........................................................................................................................................................................................................................................................
new media & society Copyright © 2002 SAGE Publications London, Thousand Oaks, CA and New Delhi Vol4(3):329–353 [1461–4448(200209)4:3,329–353;026202]
ARTICLE
Content and context: an exploration of the basic characteristics of information needs ............................................................................................................................................................................................................................................
HARRY BOUWMAN Delft University of Technology, the Netherlands ............................................................................................................................................................................................................................................
LIDWIEN VAN DE WIJNGAERT Utrecht University, the Netherlands ............................................................................................................................................................................................................................................
Abstract In this article we describe research that overcomes some of the flaws of Uses and Gratifications research by combining information need concepts with concepts from Media Choice models, and by making use of the Policy Capturing method. Using this method, we obtained indepth knowledge about the basic characteristics of information needs that can be used to explain a choice for specific media, i.e. traditional mass media and Information and Communications Technology (ICT)-based media. In two studies regarding users’ information needs in an academic context, and employees within an organizational setting, we found that the same characteristics of information need, such as topicality and context, are important predictors of media choice. The results show that more refined analyses with regard to dimensions underlying information need can contribute to insight into when and how media, including new technologies, can be successful in the emerging information society, for example, by taking context issues into account. 329
New Media & Society 4(3)
Key words context • ICT • information need • information technology • media choice • new media • policy capturing
Information needs vary strongly in nature, complexity and content. There are many alternative sources of information available, within different contexts. Some are traditional, such as newspapers and business reports, and others are new, such as intranets and electronic journals. Some are personal, such as face-to-face meetings or telephone, others less personal, for example email or annual reports. All these options have advantages and disadvantages. Some are easy to access, others are not readily available; some cost money, others are free of charge; some are easy to use, others are cumbersome; some provide a simple direct answer, others provide extra information. This brings us to our main research question. How can characteristics of information need, context and users be used to explain the choice for specific (new ICT-based) media? To deal with this research question we will first introduce some relevant concepts from Uses and Gratifications, Information Need research and from Media Choice models. These concepts are used in a contingency model of media choice. This model will be tested in our empirical research, in which we deal with two cases, one in an academic context, one in an organizational context, making use of policy-capturing methodology. The results are presented and discussed, in relation to the presented model. 1. THREE COMMUNICATION PARADIGMS Due to the interactive character of new media, it will become more and more important to take into account specific functions of media as perceived by users. The medium itself can no longer be the starting point; instead, personal factors, situations and the functions of the media for users are of prime importance, and must be taken into account, as was traditionally advocated in the Uses and Gratifications approach (Rosengren, 1974; Levi and Windahl, 1984; McQuail and Windahl, 1981; Palmgreen et al., 1985; Stappers et al., 1993). Even though Uses and Gratifications is not a single theory and was criticized (Lometti et al., 1977; Palmgreen and Rayburn, 1985; Stappers et al., 1993), there is reason to believe that the Uses and Gratifications approach is applicable to new media (Williams, 1989; Williams et al., 1988). Most new media are not designed simply to send information to a receiver, but a person has to look for information explicitly. This strongly supports the assumption of an active audience. In other words, Uses and Gratifications theory should be better suited to explain the use of new media than it could regarding those media that have traditionally been its research object. 330
Bouwman & Van de Wijngaert: Content and context
In the information seeking approach, Sepstrup (1977) defines information need as the difference between the way things are and the way that an individual would like them to be. The basic idea is that there is a perceived, i.e. subjective, difference between the available knowledge and the knowledge that is needed to perform an activity (Dervin et al., 1982; Nelissen, 1991; Renckstorf, 1994). The size and type of the difference between available knowledge and knowledge that is required determines the size and type of the information need. In addition, refinements have been made with regards to use of information (Weights et al., 1993): a need for new information; to elucidate the information already held; and to confirm the information already held. To this, two more needs can be added: a need to elucidate beliefs and values, and a need to confirm beliefs and values held (Wilson, 1996). Another categorization is proposed by Chew (1994): • orientation: seeking to discover what is happening; • reorientation: seeking to check that the person is on the right track; and • construction: seeking to form an opinion or solve a problem. In general, approaches in information need research, such as Dervin’s sense-making approach (Dervin et al., 1982; Dervin,1989, 1991; Dervin and Nilan, 1986; Vakkari et al., 1997); and Renckstorf ’s approach in which media use is conceptualized from the perspective of how it fits in with people’s behaviour (Nelissen, 1991; Renckstorf, 1994; Renckstorf et al., 1996). Both complex theories are primarily focused on conceptualization and empirically tested through qualitative research. In our view, research in the field of information need is in-depth but limited in scope, mostly caserelated and with limited external validity. In more quantitative research with regard to information need, for example in the Uses and Gratifications approach, the results are more or less tautological. The results strongly depend on the questions asked, and research in the field of information systems also shows the limited validity of the more quantitative approach. Furthermore, this research is commonly directed at only one specific medium. None of the more qualitative research approaches have significantly helped to explain media choice; nor have the more traditional Uses and Gratifications approach and the information need research approach been used in system engineering. The Social Presence concept (Short et al., 1976), Media Richness (Daft and Lengel, 1986; Trevino et al., 1990), the Social Influence model (Fulk et al., 1990), the Dual Capacity model (Eisenberg and Riley, 1993; Sitkin et al., 1992), and Media Appropriateness (Rice, 1993) offer comparable starting 331
New Media & Society 4(3)
points for the analysis of media choice. The basic assumption is that a good task/medium fit is essential for effective communication. Media richness theory approaches this assumption from a rational perspective, whereas the Social Influence model states that task and media perceptions are subjective and socially constructed (Fulk et al., 1990; Steinfield, 1991). Sitkin et al. (1992) stress the symbolic meaning of the medium. The Media Appropriateness model (Rice, 1993) stresses the multidimensional character of both media and tasks. The assumption of the Media Choice model is that organizational success is based on its ability to process information using media of appropriate richness to clarify ambiguity and reduce uncertainty (Daft et al., 1987). Equivocality refers to the assumed existence of multiple and conflicting interpretations of a specific message (Trevino et al., 1990). Richness refers to the capacity of a medium to process complex and ambiguous information. A good fit between medium and task means that a lean medium is chosen for an unequivocal message and a rich medium for a more complex one. If the wrong medium is chosen to get the message across, a mismatch occurs (Daft et al., 1987). Steinfield (1986) and Fulk et al. (1990) argue that medium characteristics and attitudes are in part socially constructed. Medium-use processes are influenced by past statements, behaviours and social norms. Consequently, in contrast to the assumptions made by rational choice models, medium choice is subject to social influence. Fulk et al. (1990) propose that determinants of medium choice are medium evaluations, task evaluations, social influence and situational factors. The importance of social influence in Fulk et al.’s model is evident from the hypothesis that social influence affects medium choice directly, and also affects medium evaluations and task evaluations. Social influence in the model is thought to consist of direct statements by co-workers, vicarious learning, group behavioural norms and social definitions of rationality. Note how, as is also argued in the Uses and Gratifications approach, past experiences influence media use (Rosengren et al., 1985). In this research, the same mechanisms of finding the right task/medium fit are relevant. The combination of a task, i.e. an information need, and media choice is investigated; however, the concept of media richness and that of task complexity cannot be used exactly as intended by the original authors. Although media richness deals with mediated communication, the actual content of communication is not taken into consideration. To argue that media can be placed on a one-dimensional scale (richness) does not do justice to the diversity of media forms that can be used to solve a particular information need, as is also argued by Rice (1993). 332
Bouwman & Van de Wijngaert: Content and context
2. A CONTINGENCY MODEL OF MEDIA CHOICE Building on the concepts that we presented in the previous section, the relation between information need and media choice is described in terms of contingency. Media choice is explained as a match between information need (i.e. the task), (user) context, and technology (i.e. media) characteristics. A graphical representation of the model is given in Figure 1. 2.1 User, group, organizational and context characteristics A first, and often used, cluster of variables contains a number of sociodemographic characteristics such as age, income, education, occupation and place in the group and organization. It is not only the individual who determines what media to use, as there will be a clear influence played by his or her peer group. For example, if there are many others who use a medium, one tends to join in. Critical mass theory strongly relates to these ideas at a meso- and macro-level of research (see Marwell and Oliver, 1993). At the individual level, the social influence model of media choice uses the same ideas (Fulk et al., 1990). In an organizational context, factors such as introduction strategy, type of organization, group size, formal hierarchy, group history, membership proximity and network participation are relevant (Benbasat and Lim, 1993; Van den Hooff, 1997). A second cluster of factors has to do with the attitudes, opinions, and ideas that users have concerning technology in general and as a specific innovation in particular. People with a positive attitude towards technology or specific innovations tend to adopt a medium sooner than people with a negative attitude. Willingness to change, creativity and innovativeness are other factors that influence the way in which people adopt media (Rogers, 1983). The third cluster of (user) context characteristics, mentioned by Bouwman and Neijens (1991), refers to experience and information-seeking behaviour. Habits strongly influence media use (Rubin, 1984, 1993). This is also related to the (dis)continuity factor mentioned by Atkin and LaRose (1994). If habits need to be changed drastically, it is very hard to get a medium adopted by a large group of people. A fourth cluster of user
• Figure 1
A contingency model of media choice 333
New Media & Society 4(3)
characteristics relates to the type and amount of equipment that a user possesses. This factor, mentioned by Bouwman and Neijens (1991), first, determines whether or not a potential user is physically able to use a medium. Secondly, there is a relationship between the possession of modern equipment and a more positive attitude towards technology. This short review of literature and meta-analysis results in a number of variables that may influence media choice. The variables that will be used in our empirical research are user characteristics, physical access in context, frequency of media use, experience with media use, attitude towards media and membership of a team. 2.2 Task characteristics Most studies characterize tasks in terms of equivocality and uncertainty. In relation to information need, this characterization falls short in terms of content. Van de Wijngaert (1996), in a research project using Q-sort analysis, has established that some of the factors influencing people’s choice of media are clearly content-related. For example, the suitability of media for topical and unique information was found to be relevant to media choice. Alongside topicality and uniqueness, the possibility to perform transactions and/or to communicate; the nature of the needs (i.e. quantitative or qualitative); and the context in which needs emerge, were also found to be relevant. These variables are included in our empirical research. 2.3 Media (or technology) characteristics Atkin and LaRose (1994) emphasize the type of innovation, and they distinguish between continuous and discontinuous innovations. Continuous innovations are adopted more easily than discontinuous innovations. The symbolic meaning of an innovation can also influence the adoption process. The type of innovation is also mentioned by Bouwman and Neijens (1991) and Van den Hooff (1997), who use the ideas of Rogers (1983), characterizing innovations in terms of relative advantage, compatibility, complexity, reliability and observability. Other characteristics of a technology are interactivity, user-friendliness, the type and number of services, costs and transparency. The types of services provided by a medium are given much attention in Bouwman and Neijens (1991). They distinguish information retrieval services, both topical and stable information, communication services, i.e. email, transaction services, banking, ordering, shopping and entertainment services (i.e. games). Benbasat and Lim (1993) define technological characteristics in terms of the level of support, facilitation and improvement of design. Bouwman and Neijens (1991) mention marketing as a factor that can influence the success or failure of a service. As they see it, marketing involves the availability and promotion of trigger, or so called 334
Bouwman & Van de Wijngaert: Content and context
‘killer’ applications, the degree to which a service is introduced on a large scale, information provision and the quality of the help-service. These studies show that using a one-dimensional scale to explain people’s choice of media is far from adequate. Likewise, Rice (1993) argues that comparisons of media are generally limited to rankings rather than multidimensional approaches. In this study, media are regarded as black boxes: we can only see the media that could possibly, or would eventually, be chosen. 3. POLICY CAPTURING In our empirical research we make use of the Policy Capturing method (Rossi and Nock, 1982), which is a method for studying choice. Policy Capturing, also known as Factorial Survey or Vignette Studies, combines the advantages of multivariate experimental designs with sample survey procedures. Policy Capturing borrows and adapts the concept of manipulation from the experimental tradition. From the survey tradition it borrows the greater richness of detail and complexity that characterizes reallife circumstances. It is a method that can be used to uncover the principles that lie behind human evaluation. The basic idea behind Policy Capturing is to present people with contrived hypothetical situations. In these situations an information need emerges. These situations, or cases, are developed by combining characteristics of the information need and context. In the next section, a detailed description of how cases are formed is presented. Consequently the following three issues can be related: (1) differences between users and user contexts can be measured; (2) differences between tasks and contexts can be varied artificially and systematically; and (3) differences in media choices can be measured by asking what medium respondents would choose to perform a certain task. Accordingly, it is possible to determine who uses which medium for what purpose. More generally, it is now possible to find out what characteristics of information need influence people’s use of media, while controlling differences between users and contexts. One of the biggest advantages of the Policy Capturing method is that media are regarded as black boxes. This choice is based on the perceived capacities of the medium, in accordance with the social influence model and the symbolic meaning of a medium. It is not the objective possibilities and limitations of the medium that are central, but the perceptions of these possibilities and limitations. In practice, a questionnaire presents respondents with a description of a situation (i.e. a case) in which an information need emerges. Respondents 335
New Media & Society 4(3)
are asked which type of medium they would consider and which ones they would eventually choose to solve the problem. Furthermore, the questionnaire consists of questions that relate to the (user) context in which media can be used, and several questions on socio-demographical variables as well as questions on the use of several media. Other Policy Capturing studies in relation to new media can be found in Martocchio et al. (1993) and Webster and Trevino (1995). Because choice is binary (either a medium is chosen, or it is not), the collected data were examined using (multilevel) logistic regression. 4. CASES 4.1 Case I: consumer context – the questionnaire The questionnaire consists of three parts: first, questions on usage characteristics, then the cases and finally some questions on sociodemographical variables. The questions on media use, with regard to frequency of media use, experience and attitude, are measured on an ordinal level. The questions dealing with social demographics are related to age, gender and subject of study. The starting point in the creation of a hypothetical situation are the dimensions, i.e. the variables that define what characterizes a situation. The levels of a dimension are similar to the values of a variable. The combination of the levels of all dimensions, i.e. the values of all variables, characterize a situation. The set of all possible combinations of all levels in all dimensions is called the factorial object universe (Rossi and Nock, 1982). The information needs in this study were based on four dimensions, i.e. variables, each with two levels, i.e. values: • topicality: topical and stable; • uniqueness: unique and common; • interaction: pure information need and information need with need for communication and/or transaction; and • context: home and university. The final set of cases consists of ten different types of needs. Table 1 shows an overview of all the cases that were used in the research. As can be derived from Table 1, not all of the 16 possible combinations of levels led to real-life situations. Although cases can be made, they do not always result in credible situations, and therefore present unrealistic answers. This is the reason why we have omitted these cases. Furthermore, several cases were constructed for each type of need. The cases were designed in such a way that for every case there was an alternative case that differed on only one dimension. For example: one need was to find out what movies are being shown at the cinema while at university, and another was to find out the same thing while at home. The only difference between the two 336
• Table 1
Overview of cases used in policy capturing study
TOPICALITY AND
UNIQUENESS AND
CONTEXT
INTERACTION
Unique university
General university
General home
Topical trans/com
No realistic cases
No realistic cases
No realistic cases
No realistic cases
Stable trans/com
1a. Order brochure on scholarship from home 1b. Talk to expert on scholarship
2a. Order brochure on scholarship fron university 2b. Talk to expert from big company on internship
No realistic cases
No realistic cases
Stable info
3a. Your grandmother wants to know train departure for difficult question from home 3b. Find picture of old airplane for nephew from home 3c. Need general information on scholarship 3d. Telephone number of friend who has moved away
4a. Find book which is not available at own university
5a. Find books while at university
4b. Find picture of old airplane from university
5b. Find translation of word
6a. Grandmother wants to know easy train question from home 6b. Find telephone number of friend while at home
4c. Find information on big companies for internship 4d. Difficult question on train departure from university
5c. Find telephone number of friend while at university
6c. Find recipe for dinner
7a. Train departure while at home and cable broken
8a. Train departure while at university and cable broken
9a. Find weather while at university
7b. Find information on terrorist attack while family on holiday there
8b. Track down news on revolutionary new invention
9b. Follow news on revolutionary breakthrough 9c. Find out what movies are on at the cinema while at university
10a. Find out what movies are on at the cinema while at university 10b. Find weather while at home 10c. Follow news in general while at home
Topical info
337
Bouwman & Van de Wijngaert: Content and context
Unique home
New Media & Society 4(3)
cases was the context dimension. Each respondent received one case from each combination. The ten cases were chosen in such a way that only one case from each subject was presented. An example of a case that was presented is: Suppose, during a lecture break, you and your fellow students decide to go to a movie tonight. You do not know what movies are being shown. How do you find out which movies you can go to?
Using a multiple-choice question, the respondent was asked which medium he or she would consider and eventually choose. Several other needs for information, with varying characteristics, were presented in the same way. For example, the same cinema case was presented in a domestic context. 4.2 Respondents Although a random sample from the Dutch population would have provided the best opportunity to generalize, it can be questioned whether meaningful information in relation to the research question could have been obtained from such a sample. For example, very few people at the time fieldwork was executed in the sample had physical access to the internet. As a consequence, for many people using new media (which this research is mainly about) was not a realistic option. Therefore, it was important to choose a group of respondents that was relatively familiar with the possibilities of new media. For this research we chose Dutch university students as a source of information. Moreover, the goal of the research was to find out how several factors influence choice, i.e. the pattern, and not what the Dutch public thinks of the new media. The only question that remained unanswered was whether this pattern is the same for the students and other sections of the population. The final sample consisted of 538 students taken from nine disciplines studying more than 40 subjects and attending ten different universities throughout the Netherlands. The sample consisted of 55 percent male and 45 percent female students and this is in accordance with proportions given for the population of Dutch students (CBS, 1997). The age of the students varied between 17 and 31. The largest group consisted of 18- to 19-yearold students. The number of students per year gradually became smaller as the students became older. In all, the respondents can be said to provide a representative sample of Dutch university students. 4.3 Results The results of the research show that at home, students have access to most of the traditional media and that computers, including internet connection and CD-rom, are widespread among students. At the university, 338
Bouwman & Van de Wijngaert: Content and context
computers and telephones are the only two types of media that are widely available. Traditional media, such as radio and television, are frequently used among students and they use computers quite often. Other new media, such as the world wide web and email are used on a regular basis, but not as much as computers or traditional media. Roughly the same conclusion can be drawn for the level of experience. The traditional media are well known to students. They are less familiar with new media such as computers, followed by CD-rom, email and the world wide web. Still, most students stated that they were regular or experienced users of these media. We can state that on the whole, all types of media received a positive evaluation, without any real exceptions. Yet the most positive evaluation was given for the option of talking to friends, either on the telephone or faceto-face. Hierarchical cluster analysis (using internal group distance and squared Euclidean distance) of functions of the media resulted in six clusters: news media, traditional media, information media, chat media, work and play media and unused media. Looking at the research’s dependent variable, i.e. media choice, it turned out that in more than one-third of the cases, calling an expert was chosen as the means to get an answer to a question (see Table 2). The telephone is very popular among students, and it can be used for almost any purpose, with the world wide web as a good second. Least popular are videotext and CD-i. Besides looking at the number of times a medium was chosen, it is also interesting to see at what ratio media are finally chosen in relation to the number of times a medium was mentioned as a possible choice. If a medium is actually chosen when it is mentioned, it • Table 2
Possible and actual media selected to satisfy information need
Radio Television Teletext CD-I Personal computer CD-rom Videotext Email World wide web Books and references Brochures and folders Papers and magazines Telephone, friends Telephone, experts Face-to-face, friends Face-to-face, experts Other
#POSSIBLE
#ACTUAL
ACTUAL (%)
RATIO (%)
831 886 1 022 22 653 214 36 592 1 672 1 235 914 1 484 1 391 3 008 980 1 145 247
62 191 275 1 228 39 1 58 559 472 131 485 257 1 765 135 381 151
1.2 3.7 5.3 0 4.4 0.8 0 1.1 10.8 9.1 2.5 9.3 5.0 34.0 2.6 7.3 2.9
7.5 21.6 26.9 4.5 34.9 18.2 2.8 9.8 33.4 38.2 14.3 32.7 18.5 58.7 13.8 33.3 61.1
339
New Media & Society 4(3)
could mean that those media are the most accessible, or that people choose these media because they think that the chance the answer will be given is high. The most important reason to choose one medium over another was simplicity. A second reason was the speed with which an answer could be obtained, and the third concerned the chance of getting a correct answer. Low costs were not a reason for choosing a medium. 4.4 Results of logistic regression Multilevel logistic regression was used to explain the variance in media choice. For most media Pseudo R ( ≈ explained variance) lay between 25 and 30 percent. First, the primary result of the analysis was that only the media were chosen to which people had physical access within the question’s context. In other words, physical access is a necessary but insufficient condition for media choice and subsequent use. Secondly, the results of multilevel logistic regression showed that differences between information needs led to differences in media choices. We can further conclude that media choices do not depend on a single characteristic of the information need. All the characteristics that were used in this research, i.e. topicality, uniqueness, interaction and context, contributed to the explanation of media choice. It can be concluded from Table 3 that there are no two media that have the same value pattern with regard to the four information need characteristics. This means that it is necessary to look at all the characteristics of the information need to predict media choice. • Table 3
The relation between information need and media choice
CHARACTERISTICS OF THE INFORMATION TOPICALITY UNIQUENESS INTERACTION Telephone, expert World wide web Newspapers, magazines Books, reference guides Face-to-face, expert Teletext Telephone, friends Personal computer Television Face-to-face, friends Brochures and folders Radio Email CD-rom
– stable topical stable stable topical stable stable topical – stable topical – stable
unique unique common common unique common unique common common common – common unique common
com/transaction information information information – information information information information – – information com/transaction information
NEED
CONTEXT home university university university university – home home home university – – university university
A word indicates a significant ( < 0.05) relationship and the ‘direction’ of the relationship. ‘–’ means that no significant relation was found. 340
Bouwman & Van de Wijngaert: Content and context
• Table 4
The relation between user characteristics and media choice
Telephone, expert World wide web Newspapers, magazines Books, reference guides Face-to-face, expert Teletext Telephone, friends Personal computer Television Face-to-face, friends Brochures and folders Radio Email CD-rom
SEX
CHARACTERISTICS OF THE USER FREQUENCY EXPERIENCE
ATTITUDE
women – – – women – – – – – – – – –
– positive – – positive positive – – – – – – – –
– – – – – – – – positive – – – – –
– positive – – not measured positive – – – not measured – – – –
A word indicates a significant ( < 0.05) relationship and the ‘direction’ of the relationship. ‘–’ means that no significant relation was found.
Thirdly, analysis showed that there are many more significant relations for information needs than there are for differences between users. A comparison of Tables 3 and 4 demonstrates this difference. Differences between information needs explain much more about the media choices than the differences between users. Although there were not many significant relations in differences between users and media choice, it has to be said that almost all relations, including the non-significant ones, were positive. This means that the chance that a medium is chosen increases when a user states that he or she uses a medium more often, is more experienced with and/or has a more positive image of a medium. 4.5 Case II: organizational context The second case-study was conducted within a large corporation active in the field of information technology for clients in many areas, including finance, government, trade, transport and distribution, telecommunications, utility and media and manufacturing. A large number of employees work at the clients’ offices. The goal of the study was to support the development of a sales and marketing intranet for the company. The processes within this company are prescribed, as is the information necessary for these processes. Company rules describe what kind of information should be collected in which phase of the sales and marketing processes. Nevertheless, there are differences between the norm and practice. Some information is prescribed and functional, some information is necessary but not prescribed, and some prescribed information is not necessary. The information is acquired via traditional media, i.e. telephone, reports, electronic media, the internet, 341
New Media & Society 4(3)
newsgroups, email, databases; specific traditional and electronic media used within the organization and media used by the organization’s clients. The prescribed media are meetings, reports, business magazines, the internet, intranet and internal presentations of new services. Nevertheless, there are bottlenecks with regard to information provision, such as availability, quality, relevance and accessibility of information, and cumbersome interfaces of some of the information systems. Therefore a research project was initiated to focus on the fit between information need and media choice. This research project was expected to contribute to the design of a new information system dedicated to sales and marketing processes within the organization using the organization’s intranet. 4.6 The questionnaire The questionnaire had a more limited design than the one used for the previous study (case I). Questions on the position within the organization, the experience with and use of specific information systems used within the organization were posed. Next, information needs were presented. The set of cases was based on the same three dimensions used in the previous study, i.e. topicality, uniqueness and context. For the last dimension, context, an extra level was added. In addition to work and home, work on the client’s premises was added. Two more dimensions were also added: first, what kind of data was collected; quantitative data, for example performance indicators, or more qualitative information, i.e. information on companies’ strategies. The second dealt with the context in which the information was collected. Mostly the respondents in this case-study operated individually until a specific opportunity was recognized and a team was formed. We therefore added the dimension of organizational unit. The final set of dimensions used were: (1) (2) (3) (4) (5)
topicality: topical and stable; uniqueness: unique and common; context: customer premises, home, work; nature: quantitative data or qualitative evaluations; and organizational unit: individually or team.
The final set of information needs consisted of 48 cases. However, three cases were discarded because they were unrealistic. In this study, the cases were designed in the same way as the case-study presented earlier, i.e. for every case there was an alternative case that was different in only one dimension. Each respondent received a limited set of eight cases. The individual cases were randomly distributed over the sub-samples as presented to respondents. The following is an example of a case. An account manager has approached you with a possible opportunity for a client. You have a longstanding relation with this client. Together with some 342
Bouwman & Van de Wijngaert: Content and context
colleagues you gave your commitment to participate in this project. You are working at your office and you are trying to collect some data on the basis of which you can assess the opportunity. You are looking for information on HRM policy, more specifically you are interested in the number of people who work full-time, part-time and who are hired from an agency. What form of medium would you choose?
The other needs for information, with varying characteristics, were presented in the same way. 4.7 Respondents A sample of employees was selected within the organization involved in the processes for which the information systems were to be developed. A total of 55 people were asked to collaborate, 39 of whom responded positively. The sample was evenly distributed, taking into account the sectors in which the employees were working and the various positions that they held within the organization. The time that an employee was working for the organization was distributed according to population figures. There were more male than female respondents, but this was according to the distribution of men and women within the workforce. So in general this sample was representative of the employees actively involved with the relevant processes dealt with within this study. 4.8 Results Generally speaking, the employees have access to a very broad set of media: mass media, e.g. modern computer-based media, general media, e.g. internal media, and media from their organization as well as that of the client. In total, 28 alternatives were given. For analytical purposes, the media that were chosen were clustered into slightly larger categories. For example, annual reports, newsletters and reports were clustered into traditional organizational media. Two media were considered to be the most important: the internet and telephone, followed by forms of informal communication. With regard to media choice it was striking that, although a lot of media forms were considered as a possible source of information, only a few were actually chosen. Results are shown in Table 5. Some media are mentioned very frequently as a possibility to satisfy an information need, but in the end they were rarely chosen, e.g. electronic media, media that can be found at the client’s offices and mass media. Although these media were suitable for obtaining an answer to a question, only some media are physically or affectively accessible. In this light, the result of the specific organization channel, with a ratio of only 7.7 percent, was especially disappointing because this study was initiated to contribute to the further development of this channel, however much it does confirm its raison d’être. 343
New Media & Society 4(3)
• Table 5
Possible and actual media selected to satisfy information need
Internet Email Telephone Traditional organisational media Electronic organisational media Meetings (daily) Meetings (hallways) Meetings (formal) Media client Mass media
#POSSIBLE
#ACTUAL
ACTUAL (%)
RATIO (%)
182 95 147 204 208 110 119 95 258 276
71 12 39 36 16 31 22 16 18 8
26.4 4.5 14.5 13.4 5.9 11.5 8.2 5.9 6.7 3.0
39.0 12.6 26.5 17.6 7.7 28.2 18.5 16.8 7.0 2.9
Based on the figures in Table 6, Figure 2 shows how the final choices are related to the characteristics of information needs (topicality, uniqueness and nature), to differences between users and to context. Each bar shows how media choices are distributed over each value and variable. The figure clearly shows that the internet was chosen relatively often in comparison to the other media for almost all variables and values. What is also striking is that there are hardly any differences between the choices of media. Some media are chosen more often than others, but the relation between a certain media choice and differences between needs, individuals and contexts is hard to establish. In the next section, logistic regression will be used to elaborate on this. 4.9 Results of logistic regression In this case-study, logistic regression was also used to explain the variance in media choice. For most media Pseudo R is low and lies between 1 and 23 percent. The rationale behind this lies in the design of this case in comparison with the case previously presented. The most striking differences are: (1) The refined selection of media (case I: 14, case II: 28). For example, there are hardly any differences between the three different types of (intranet) channels. The same goes for specific types of presentations held within the organization under study, several information media within client organizations, or the difference between social and informal communication; (2) The rather high number of cases presented to the respondents (case I: 10; case II: 45). The high number of cases probably make it hard for the respondents to make clear distinctions between the cases and therefore also have contributed to the limited explaining power; and 344
Bouwman & Van de Wijngaert: Content and context
(3) the limited number of respondents (case I: 538, Case II: 39). This may have contributed to multilevel problems. Table 7 shows a large number of not significant relations, indicating that many media choices cannot be explained. A prediction about what medium is chosen is hard to make when a medium is only chosen a few times. The results of the logistic regression can be described from the media perspective and from the dimensions perspective. First of all the media perspective: (1) Internet and email: the most important difference between internet and email is that internet is used for common, general questions and email is used for more specific and unique questions. (2) Telephone: looking at the underlying data we can see, for example, that the telephone is used for topical and stable information, specific and common information, and qualitative and quantitative information, in different contexts and individually as well as in a team. We can conclude that the telephone is an integrated part of the working environment of our subjects. The case-study described above also showed that the telephone is a strong, multifunctional medium; (3) Business meetings: we see that they are important in cases where information needs score on dimensions such as qualitative, specific, topical and context. Taking the dimensions perspective we can see the importance of uniqueness, nature and context. Although the data do not really support the idea of a clear-cut match between information need and a specific medium, some results are still enlightening. Table 7 shows that quantitative data are collected from traditional and electronic organizational media, and qualitative data from social forms of communications. In this light, context is the aspect that best helps to explain the results. In contrast, topicality and business unit have little or no explanatory power. 5. CONCLUSION AND DISCUSSION How can the characteristics of information need, context and differences between users be used to explain the choice in favour of specific (new ICTbased) media? The medium that is eventually used depends on a variety of factors: the characteristics of the need for information; the characteristics of the person asking a specific question; and the context in which people have, or do not have, (physical) access to media. The research shows that the characteristics of information need and the context of the user explains more than the characteristics of the user. 345
New Media & Society 4(3)
• Table 6 The relation between information need and media choice. The table shows media in the rows. The columns present counts, percentages within final choice and percentages within the variables topicality, uniqueness, nature, unit and context
TOPICALITY STABLE
TOPICAL
UNIQUENESS COMMON
UNIQUE
Internet
Count % within final choice % within variable
39 54.9 26.7
32 45.1 26.0
46 64.8 34.8
25 35.2 18.2
Email
Count % within final choice % within variable
8 66.7 5.5
4 33.3 3.3
3 25.0 2.3
9 75.0 6.6
Telephone
Count % within final choice % within variable
24 61.5 16.4
15 38.5 12.2
19 48.7 14.4
20 51.3 14.6
Traditional organisational media
Count % within final choice % within variable
23 63.9 15.8
13 36.1 10.6
19 52.8 14.4
17 47.2
Electronic organisational media
Count % within final choice % within variable
10 62.5 6.8
6 37.5 4.9
6 37.5 4.5
10 62.5 7.3
Meetings (daily)
Count % within final choice % within variable
18 58.1 12.3
13 41.9 10.6
8 25.8 6.1
23 74.2 16.8
Meetings (hallways)
Count % within final choice % within variable
7 31.8 4.8
15 68.2 12.2
10 45.5 7.6
12 54.5 8.8
Meeting (formal)
Count % within final choice % within variable
7 43.8 4.8
9 56.3 7.3
5 31.3 3.8
11 68.8 8.0
Media client
Count % within final choice % within variable
8 44.4 5.5
10 55.6 8.1
10 55.6 7.6
8 44.4 5.8
Mass media
Count % within final choice % within variable
2 25.0 1.4
6 75.0 4.9
6 75.0 4.5
2 25.0 1.5
The first case-study that we conducted was more convincing than the second one in relation to our assumption that dimensions of information need explain media choice. But still some patterns in the second study support the basic concept. Although the second case is not as convincing as the first, we included this case because we learned a great deal in terms of how to design this type of study more carefully. Despite using the same 346
Bouwman & Van de Wijngaert: Content and context
(Table 6 cont.)
NATURE QUANTITATIVE QUALITATIVE
UNIT INDIVIDUAL TEAM
CONTEXT HOME CLIENT
OFFICE
FINAL CHOICE
36 50.7 25.7
35 49.3 27.1
41 57.7 28.9
30 42.3 23.6
43 60.6 44.3
11 15.5 12.8
17 23.9 19.8
4 33.3 2.9
8 66.7 6.2
5 41.7 3.5
7 58.3 5.5
4 33.3 4.1
3 25.0 3.5
5 41.7 5.8
12
18 46.2 12.9
21 53.8 16.3
22 56.4 15.5
17 43.6 13.4
9 23.1 9.3
15 38.5 17.4
15 38.5 17.4
39
30 83.3 21.4
6 16.7 4.7
17 47.2 12.0
19 52.8 15.0
14 38.9 14.4
8 22.2 9.3
14 38.9 16.3
13 81.3 9.3
3 18.8 2.3
7 43.8 4.9
9 56.3 7.1
8 50.0 8.2
4 25.0 4.7
4 25.0 4.7
16
15 48.8 10.7
16 51.6 12.4
15 48.4 10.6
16 51.6 12.6
7 22.6 7.2
19 61.3 22.1
5 16.1 5.8
31
3 13.6 2.1
19 86.4 14.7
13 59.1 9.2
9 40.9 7.1
1 4.5 1.0
12 54.5 14.0
9 40.9 10.5
22
8 50.0 5.7
8 50.0 6.2
6 37.5 4.2
10 62.5 7.9
1 6.3 1.0
4 25.0 4.7
11 68.8 12.8
16
9 50.0 6.4
9 50.0 7.0
11 61.1 7.7
7 38.9 5.5
7 38.9 7.2
6 33.3 7.7
5 27.8 5.8
18
4 50.0 2.9
4 50.0 3.1
5 62.5 3.5
3 37.5 2.4
3 37.5 3.1
4 50.0 4.7
1 12.5 1.2
8
71 26.4
4.5
14.5 36 13.4
5.9
11.5
8.18
5.9
6.7
3.0
concepts and research approach, both case studies differ considerably in their individual design: number of cases, number of alternative media considered and number of respondents. Subtle balances between these three elements should exist. We suspect that we used too many cases in the second casestudy, that differences between media were not clear enough, and that too few respondents were available. The limited number of respondents may 347
New Media & Society 4(3)
• Figure 2 • Table 7
Relation between information needs, differences between users and context The relation between information need and media choice (after logistic regression)
CHARACTERISTICS OF THE INFORMATION NEED TOPICALITY UNIQUENESS NATURE UNIT CONTEXT Telephone Email Telephone Traditional organisational media Electronic organisational media (Channel) Meetings (daily) Meetings (hallways) Meeting (formal) Media client Mass media
– – – –
common unique* – –
– – – quantitative
– – – –
home – office, client* home, office*
–
–
quantitative
–
–
– topical* – – topical*
unique – – – –
– qualitiative – – –
– – – – –
client client, office office – –
A word indicates a significant ( < 0.05, * indicates significance at < 0.1) relationship and the ‘direction’ of the relationship. ‘–’ means that no significant relation was found.
348
Bouwman & Van de Wijngaert: Content and context
have produced multilevel problems. Too much communality is caused by respondents’ characteristics. Furthermore, the list of options available is too specific. Some of the media included in the list of relevant media were very similar and were only a proprietary version of a more general category, or were another term for a face-to-face meeting. In spite of these limitations, we have found some interesting and promising patterns, albeit not significant ones. These patterns are in line with the results of the first case-study. Based on the results of the two cases there is reason to believe that media choice can be explained from characteristics of the information need and the context in which users are. The model as presented in Figure 1 is a valid one, although it does need to be refined. From the results of the research it can be concluded that people need to overcome several thresholds before they start using a medium. These thresholds, or forms of accessibility are as follows. (1) Physical accessibility: this relates to the question of whether a medium is physically and financially accessible in a specific context: at home, at work or on a client’s premises. This form of accessibility is a necessary but insufficient condition for media use. In the future access in a mobile context to specific media will also play a role. (2) Suitability: can the medium provide an answer to the question? Here a difference with communication media can be found. For communication media, the question is whether a message can be properly conveyed. For information needs, the question is whether the answer can be obtained using a specific medium. The question of whether the medium is appropriate for conveying the answer also needs to be answered. (3) Affective accessibility: this form of accessibility relates to the question of whether a medium is part of everyday life, as was also proposed by Fulk et. al. (1990) when discussing the social influence model. Does a busy CEO like to get a quick answer from the company intranet or does he or she prefer to have some social contact and ask a team member? These forms of accessibility can be related to the three clusters of variables used in the basic model (see Figure 3). Media choice does not depend solely on the (user) context, task or technology. All three areas should match; physical access, suitability and affective accessibility form the bridges between the three areas. The more general question that was raised was whether a theory that is developed for the explanation of mass communication media use, i.e. Uses and Gratifications, can also be used to explain the use of new media. The 349
New Media & Society 4(3)
• Figure 3
Three threshold model
empirical research confirms that the Uses and Gratifications approach is suited to explain media choice, although there are differences between traditional media and the media that were the object of this research. Most new media are not simply used to send information to a receiver. The receiver has to seek for information explicitly. This strongly supports the assumption of an active audience, which is a central concept of the Uses and Gratifications approach. Support was also found for the contingency theory describing the relation between information need and media choice; in this research we paid much more attention to the content of the communication than most other gratification typologies. The ‘traditional’ typologies have a very general character: for example, distinctions are made between unequivocality and uncertainty. In this research, need was characterized on a more specific, operational level. Issues such as topicality, uniqueness, interactivity and context are considered to be basic characteristics of information need. This type of characterization has not been explored in earlier research. Content and context provide fruitful starting points for the characterization of information needs. In general, we can conclude that research in the field of information need in relation to media choice can solve some of the problems of traditional Uses and Gratifications research. The tautological nature of the problem and the empirical demonstration of audience activity within a specific context and media choice especially can be explained and predicted by making use of Policy Capturing methodology. The design of specific cases should be carefully considered, striving for a balance between the number of cases, 350
Bouwman & Van de Wijngaert: Content and context
respondents and media included in the design of the specific case. Research in the field of information needs could benefit from this approach, because it opens opportunities up to generalize findings from the sense-making approach and the media-use-as-social-activity approach. Furthermore, the scope of analysis can be expanded to include the need for entertainment as well as other concepts that are being used within the Uses and Gratification approach. References Atkin, D. and R. LaRose (1994) ‘A Meta-Analysis of the Information Services Adoption Literature: Lessons to Be Learned From Cable and Telephony’, in J. Hanson (ed.) Advances in Telematics, Vol. 2, pp. 91–110. Norwood, NJ: Ablex Publishing. Benbasat, I. and L. Lim (1993) ‘The Effect of Group, Task, Context and Technology Variables on the Usefulness of Group Support Systems: A Meta-Analysis of Experimental Studies’, Small Group Research 24(4): 430–62. Bouwman, H. and P. Neijens (1991) ‘Een Meta-Analyse van Videotex-Literatuur: Een Aanzet tot een Acceptatiemodel voor de Consumentenmarkt’(A Meta-Analysis of Videotex Literature: An Impulse Towards an Adoption Model for the Consumer Market), Massacommunicatie 19(2): 134–48. CBS (1997) Statistisch Jaarboek 1997 (Statistical Yearbook 1997). Voorburg: Centraal Bureau voor de Statistiek. Chew, F. (1994) ‘The Relationship of Information Needs to Issue Relevance and Media Use’, Journalism & Mass Communication Quarterly 71(3): 676–88. Daft, R.L. and R.H. Lengel (1984) ‘Information Richness: A New Approach to Managerial Behaviour and Organizational Design’, in B.M. Staw and L.L. Cummings (eds) Research in Organizational Behaviour, pp. 191–233. Greenwich, CT: JAI Press. Daft, R.L. and R.H. Lengel (1986) ‘Organizational Information Requirements, Media Richness and Structural Design’, Management Science 32(5): 554–71. Daft, R., R.H. Lengel and L. Trevino (1987) ‘Organizational Information Requirements, Media Richness and Structural Design’, MIS Quarterly 11: 355–66. Dervin, B. (1989) ‘Users As Research Inventions: How Research Categories Perpetuate Myths’, Journal of Communication 39(3): 216–32. Dervin, B. (1991) ‘Information As Non-Sense; Information As Sense. The Communication Technology Connection’, in H. Bouwman, P. Nelissen and M. Vooijs (eds) Tussen Vraag En Aanbod. Optimalisering Van De Informatievoorziening, pp. 44–59. Amsterdam: Otto Cramwinckel. Dervin, B. and M. Nilan (1986) ‘Information Needs and Uses: A Conceptual and Methodological Review’, Annual Review of Information Science and Technology 21: 3–33. Dervin, B., T.L. Jacobson and M.S. Nilan (1982) ‘Measuring Aspects of Information Seeking: A Test of Quantitative/Qualitative Methodology’, in Communication Yearbook Vol. 5, pp. 419–46. Newbury Park, CA: Sage. Eisenberg, E.M. and P. Riley (1993) ‘Organizational Symbols and Sensemaking’, in G.M. Goldhaber and G.A. Barnett (eds) Handbook of Organisational Communication, pp. 131–150. Norwood, NJ: Ablex. Fulk, J., J. Schmitz and C. Steinfield (1990) ‘A Social Influence Model of Technology Use’, in J. Fulk and C. Steinfield (eds) Organisations and Communication Technology, pp. 117–40. Newbury Park, CA: Sage. Levi, M.R. and S. Windahl (1984) ‘Audience Activity and Gratifications. A Conceptual Clarification and Exploration’, Communication Research 11(1): 51–78. 351
New Media & Society 4(3)
Lometti, G., E.B. Reeves and C. Bybee (1977) ‘Investigating the Assumptions of Uses and Gratifications Research’, Communication Research 4(3): 321–38. McQuail, D. and S. Windahl (1981) Communication Models for the Study of Mass Communications. New York: Longman. Martocchio, J., J. Webster and C. Baker (1993) ‘Decision-Making in Management Information Systems Research: The Utility of Policy Capturing Methodology’, Behaviour & Information Technology 12(4): 238–48. Marwell, G. and P. Oliver (1993) The Critical Mass in Collective Action: A Micro-Social Theory. New York: Cambridge University Press. Nelissen, P.W.M. (1991) Het Omgaan met Kennis en de Vraag Naar Voorlichting (Dealing with Knowledge and the Demand for Public Information). Nijmegen: Instituut voor Toegepaste Sociale Wetenschappen. Palmgreen, P. and J.D. Rayburn (1985) ‘An Expectancy-Value Approach to Media Gratifications’, in K.E. Rosengren, L.A. Wenner and P. Palmgreen (eds) Media Gratifications Research: Current Perspectives, pp. 61–71. Beverly Hills, CA: Sage. Palmgreen, P., L.A. Wenner and K.E. Rosengren (1985) ‘Uses and Gratifications Research: The Past Ten Years’, in K.E. Rosengren, L.A. Wenner and P. Palmgreen (eds) Media Gratifications Research: Current Perspectives, pp. 11–37. Beverly Hills, CA: Sage. Renckstorf, K. (1994) Mediagebruik Als Sociaal Handelen (Media Use as Social Behaviour). Nijmegen: Instituut voor Toegepaste Sociale Wetenschappen. Renckstorf, K., D. McQuail and N. Jankowski (1996) Media Use As Social Action. London: John Libbey. Rice, R.E. (1993) ‘Media Appropriateness Using Social Presence Theory to Compare Traditional and New Organizational Media’, Human Communication Research 19(4): 451–84. Rogers, E.M. (1983) Diffusion of Innovations. New York: Free Press. Rosengren, K.E. (1974) ‘Uses and Gratifications: A Paradigm Outlined’, in J.G. Blumler and E. Katz (eds) The Uses of Mass Communications, pp. 269–286. Beverly Hills, CA: Sage. Rosengren, K.E., L.A. Wenner and P. Palmgreen (1985) Media Gratifications Research: Current Perspectives. Beverly Hills, CA: Sage. Rossi, P.H. and L. Nock (1982) Measuring Social Judgements. Beverly Hills, CA: Sage. Rubin, A.M. (1984) ‘Ritualised and Instrumental Television Viewing’, Journal of Communication 34(2): 67–77. Rubin, A.M. (1993) ‘Audience Activity and Media Use’, Communication Monographs 60: 98–105. Sepstrup, P. (1977) Consumption of Mass Communication: Construction of a Model on Information Consumption Behaviour. Aarhus: Institut for Markedsokonomie. Short J., E. Williams and B. Christie (1976) The Social Psychology of Telecommunications. London: Wiley. Sitkin, S.B., K.M. Sutcliffe and J.R. Barrios-Choplin (1992) ‘A Dual Capacity Model of Communication Media Choice in Organisations’, Human Communication Research 18(4): 563–98. Stappers, J.G., A.D. Reijnders and W.A.J. Möller (1993) De Werking Van De Massamedia: Een Overzicht Van Inzichten (Efficacy of Mass Media: An Overview of Insights). Amsterdam: Arbeiderspers. Steinfield, C. (1986) ‘Computer-mediated Communication in an Organizational Setting. Explaining Task-related and Social-emotional Uses’, in M. McLaughlin (ed.) Communication Yearbook, Vol. 9, pp. 777–804. Newbury, CA: Sage. 352
Bouwman & Van de Wijngaert: Content and context
Steinfield, C. (1991) ‘Communicatie Via Computers Binnen Organisaties: Theoretische Kaders En Onderzoeksrichtingen’, (Computer Mediated Communication: Conceptual Framework and Research Orientation) in H. Bouwman, P. Nelissen, and M. Vooijs (eds) Tussen Vraag En Aanbod. Optimalisering Van De Informatievoorziening, (Between Supply and Demand: Optimising Information Provision) pp. 141–53. Amsterdam: Otto Cramwinckel. Trevino, L.K., R.L. Daft and R.H. Lengel (1990) ‘Understanding Managers’ Media Choices: A Symbolic Interactionist Perspective’, in J. Fulk and C. Steinfield (eds) Organisations and Communication Technology, pp. 71–94. Newbury Park, CA: Sage. Vakkari, P., R. Savolainen and B. Dervin (1997) Information Seeking in Context. London: Taylor Graham. van de Wijngaert, L. (1996) ‘A Users’ Perspective on Information Services’, Information Services & Use 16(2): 103–22. van de Wijngaert, L. (1999) Matching Media: Information Need and New Media Choice. Enschede: Telematica Instituut. van den Hooff, B. (1997) Incorporating Electronic Mail: Adoption, Use and Effects of Electronic Mail in Organizations. Amsterdam: Otto Cramwinckel. Webster, J. and L.K. Trevino (1995) ‘Rational and Social Theories As Complementary Explanations of Communication Media Choices: Two Policy-Capturing Studies’, Academy of Management Journal 38(6): 1544–72. Weights, W., G. Widdershoven, G. Kok and P. Tomlow (1993) ‘Patients’ Information Seeking Actions and Physicians’ Responses in Gynaecological Consultations’, Qualitative Health Research 3(4): 398–429. Williams, F. (1989) ‘De Nieuwe Media: Enkele Conceptuele Parameters’, (New Media: Some Conceptual Parameters) in H. Bouwman and N. Jankowski (eds) Interactieve Media Op Komst, (The Breakthrough of Interactive Media) pp. 28–38. Amsterdam: Otto Cramwinckel. Williams, F., R.E. Rice and E.M. Rogers (1988) Research Methods and the New Media. New York: Free Press. Wilson, T. (1996) ‘Information Needs and Uses: Fifty Years of Progress?’, in B.C. Vickery (ed.) Fifty Years of Progress, a Journal of Documentation Review, pp. 15–52. London: ASLIB. HARRY BOUWMAN is an associate professor at Delft University of Technology, Faculty of Technology, Policy and Management. He is author and editor of several books in the field of Multimedia, ICT and Telecommunications. He has contributed to national and international scientific and business journals and is editor of Trends in Communication, a journal that deals with the newest developments in the field of communication and ICT. Recent publications are Silicon Valley in de Polder (Silicon Valley in the Polder) and Communicatie in de Informatiesamenleving (Communication in the Information Society). Address: Faculty of Technology, Policy and Management, Delft University of Technology, PO Box 5015, 2600 GA Delft, the Netherlands. [email:
[email protected]] LIDWIEN VAN DE WIJNGAERT is an assistant professor at Utrecht University, Faculty of Mathematics and Computer Sciences. She is author and editor of books in the field of Information Behaviour. Her recent publications discuss new information and communication technologies from a user perspective. Address: Faculty of Mathematics and Computer Science, Institute of Information and Computing Sciences, Utrecht University, PO Box 80.089, 3508 TB Utrecht, the Netherlands. [email:
[email protected]]
353
