Resource dependencies in mobile services value networks Mark de Reuver and Harry Bouwman, Delft University of Technology
Abstract— As mobile infrastructures of 3G and beyond are evolving rapidly, the next generation of mobile Internet services is on its way. Developing and commercializing these mobile Internet services requires a broad set of resources and capabilities ranging from the basic telecommunication network to specific applications, user data and interesting content. As operators, content providers and application developers do not possess all these resources themselves, they need to act collectively in complex value networks. This paper assesses what resource dependencies are most critical in mobile Internet services value networks, and how the level of perceived dependency differs among the various types of actors in the mobile domain, i.e. operators, application providers, content providers, and consultancies. We do so by applying resource dependence theory on the mobile Internet services domain, and by analyzing the results of a survey among 97 practitioners and experts. The results of a confirmatory factor analysis using Amos 7.0 confirm our proposition that resource dependencies can be clustered in those related to access to the network; access to the customer; access to content; and access to applications. Moreover, we found that the level of perceived dependency is significantly different among the actor types. Our results provide a basis for further research on resource dependencies in mobile value networks, as well as guidance for actors in the field on what dependencies to take into account when developing innovative business models and services.
I. INTRODUCTION
A
S rapidly evolving mobile infrastructures of 3G and beyond enable ever-increasing data rates, the next generation of mobile Internet services is on its way. Driven by advanced middleware and application platforms that enable context awareness and personalization, novel service concepts are enabled that are generally expected to provide high added value to consumers [1]. To develop, implement and commercialize such advanced services, a range of resources and capabilities is required. These can be found on the infrastructure level, i.e. the telecommunication network, handsets, and billing infrastructure, and on the middleware and application level, i.e. application platforms, content adaptation platforms, content. Typically, such resources are dispersed among the various actors in the value network, including the operator, application provider, content provider, and handset provider. In resource dependence theory, the behavior of organizations is considered to be influenced by its perceived level of dependency upon its environment for attaining
Manuscript received March 29, 2008. Mark de Reuver and Harry Bouwman are with Delft University of Technology, PO Box 5015, 2600 GA Delft, The Netherlands (phone: +31 15 278 1920; e-mail:
[email protected]).
essential resources [2]. In the mobile Internet services arena, resources dependencies are often dealt with by organizing collective action in complex value networks. Proper governance mechanisms are required for organizing this collective action and to manage the interdependencies, and to deal with potentially conflicting strategic interests of the actors. While asymmetric resource dependencies often lead to power differences [2] implying authority-based governance, more equally distributed levels of dependency may trigger the formation of close trust-based governance. As such, insight in resource dependencies helps to understand how actors (can) behave in value networks, and how these value networks evolve over time. The objective of this paper is to assess what resource dependencies are most critical in mobile services value networks, and how the level of perceived dependency differs among operators, application providers and content providers. To do so, we analyze the results of a survey among 96 practitioners and experts in the mobile Internet services domain. The next section discusses the theoretical background of the study, i.e. resource dependence theory. Next, we sketch the domain of the study including typical resources that organizations depend on to develop and offer mobile Internet services. After that, we present the methodology, followed by the main results. Finally, we discuss limitations to the approach and present the conclusion and next steps for research. II. BACKGROUND A. Resources Wernerfelt [3] defines resources as `those (tangible and intangible) assets which are tied semi-permanently to the firm’. This means that resources are not only the physical attributes of a firm, but they can also be of intangible nature. Barney [4] specifies this definition by adding that resources should be valuable to the firm: `all assets, capabilities, organizational processes, firm attributes, information, knowledge, etc. controlled by a firm that enable the firm to conceive of and implement strategies that improve its efficiency and effectiveness’. Das and Teng [5] classify resources into property-based resources, such as human resources, patents, contract, copyrights, trademarks and physical resources, and knowledge-based resources, such as organizational resources, and technological and managerial resources. Barney [4] notes that until the 1980s, most strategic
research focused on opportunities and threats in the environment of organizations, assuming implicitly that all firms within an industry have identical resources or that resources are highly mobile. Barney proposes two alternate, more realistic assumptions, being that firms do not have homogenous resources, and that these resources may not be perfectly mobile across firms. Implicitly, these assumptions predict that the resources needed to develop, implement and commercialize services may not be available within a single firm. Moreover, the resources may not be perfectly mobile, so a firm lacking specific resources may not be able to acquire these resources over time. As a result, organizations become dependent upon each other in order to offer services. B. Resource dependency While Barney’s resource based view typically focuses on intrafirm resources to explain firm performance, Pfeffer and Salancik’s [2] resource dependence theory takes an external perspective to explain firm behavior. Their theory projects that organizations need several resources for their survival, part of which is only available in their environment. This makes the actions and outcome of organizations interdependent. These interdependencies can be competitive, in case the actors need the same resources for their survival, or symbiotic, in case the actors require each others’ outputs for their own survival. Interdependencies among two organizations are not necessarily symmetric and balanced, as the level of dependence is a function of three factors. The first is the importance of the resource, i.e. whether the resource is essential for survival of the organization and the relative magnitude of the exchange. The second is the extent to which the external organization has discretion over the allocation and use of the resource. The third factor is whether there are little alternatives to acquire the resource. An organization is typically asked for something in return for obtaining a resource from an external organization. For example, if an organization needs a product from its supplier, the supplier will ask for a financial payment. In this way, organizations are influenced by those who control the resources they need. In case the interdependence between organizations is asymmetric, a power difference emerges. The main argument from Pfeffer and Salancik [2] is that organizations are not self-directed and autonomous, but that they are externally controlled by other organizations in their environment on whose resources they are dependent. So, to understand the behavior of an organization, insight is needed in the resource dependencies an organization perceives towards actors in its environment. One response to organizational interdependence is merger, but these can be undesirable, impossible or infeasible. In that case, social coordination of interdependent actors is a possibility, which is more flexible than merging as the relations can be altered easier. Social coordination can be established by having interlocking directorates, centralized structures as associations and cartels, normative coordination of
interdependence and joint ventures. Solutions to interdependence generally lead to actions that create new interdependence, as external organizations may respond by bundling their power in turn. Resource dependence theory is useful to explain how actors in a value network interact and organize their collective action. The theory explains that organizations need resources from external organizations, and that this creates external control over these organizations. Organizations may respond to this external control, and to the uncertainty about the dependence relation, by seeking social relations with organizations in their environment. Furthermore, the theory explains that there may be asymmetric and unbalanced dependency relations between organizations that require each others’ resources. This may lead to power asymmetries between the organizations, or by having one actor dominating the others in the value network. Finally, the theory predicts that organizations will behave such as to limit their dependence on other organizations. Therefore, the relations and interdependencies of the organizations will change over time, which means that value networks will be dynamic. Summarizing, we assert that insight in resource dependencies between actors in value networks helps in understanding how they interact while developing, implementing and commercializing services. More specifically, our hypothesis is that asymmetric resource dependencies lead to power differences in value networks. These power differences are a necessary condition for authority-based governance that organizes collective action. III. RESOURCES IN THE MOBILE INTERNET SERVICES DOMAIN In the past decade, resource dependencies among actors in the mobile Internet services domain have increased dramatically. Ten years ago, when only voice services were being offered, the mobile telecommunications value chain was fairly simple, comprising only network operators and equipment manufacturers. Operators controlled most of the activities, i.e. operation and access, the sales and after-sales of handset and services, and end-user billing [6]. As such, operators controlled both the wholesale side of the value chain (i.e. the communications network) and the retail side (i.e. customer interaction and support services) [7]. The introduction of mobile data services disrupted this well-organized value chain. Data services added a number of activities to the value chain, such as Internet access and development and provisioning of middleware, content, applications, platforms and portals [6, 8]. As a result, actors were entering the mobile services domain from the content, IT and consumer electronics sectors [9]. Because the increased number of relationships between the actors today go beyond the structure of a linear chain, it makes more sense to see the mobile data services industry as a value network [10]. For mobile Internet services, several types of resources upon which actors depend can be identified. We propose that they can be clustered in four categories, i.e. relating to the network, users, application and content.
In terms of network related resources, firstly, a physical network infrastructure is required, consisting of antennas, base stations and core network. Typically, this physical infrastructure is provided by network manufacturers such as Ericsson, Huawei, Lucent-Alcatel and Nokia-Siemens. Secondly, this infrastructure has to be operated on a day-to-day basis, i.e. network traffic needs to be handled. This connectivity is typically offered by the network operator such as T-Mobile, Orange and Vodafone. Alternatively, Mobile Virtual Network Operators (MVNOs) can play the role of agent between the network operator and end customers [11]. Thirdly, end-users require handsets to receive services, which are provided by handset providers such as Nokia, Motorola, Samsung and Sony-Ericsson. Generally, access to the end user and user data are essential resources for any company as the customer relation, transaction and data are essential for any e-business model [12]. Firstly, users need to be identified and authenticated to personalize services and to be able to identify the consumer. Especially for mobile banking services, secure and reliable authentication methods are required. Typically, this is done through SIM card based methods provided by the network operator, but alternative web services based approaches are emerging as well. Secondly, billing facilities are required for charging the user for those services that involve premium priced content. The billing and collections provider “issues bills (or the equivalent) and arranges for collection of payments from customers” [11], either through prepaid or post-paid billing arrangements. Accounting and dividing the revenues among the actors involved in offering the service is usually carried out by the same actor. At the moment, it is usually the network operator who plays the role of billing provider, although other actors in the fixed Internet and banking domain are also adopting this role. Thirdly, customer support is often required for mobile Internet services. While multiple actors can be accountable for proper functioning of the service and fair billing, there is often one point of contact available to the end-user in case of problems. Fourthly, data about the end-user is required for many facets of service delivery. Information on which handset and browser is being used is required for a proper presentation of the content to ensure a good service experience. Moreover, to allow context-aware services to be provided, dynamic information about the context of the user is needed. An important example of this type of information is location information, which can be provided by the network operator by triangulating the position of the user, or alternatively through GPS technology. Most types of services require applications and platforms, both to run on user devices and at the service providers’ end. Specifically, content adaptation platforms are often required to adapt web-based content to a WAP-based format that suits the specific user device. And users may require micro-browsers and Java applications to access services. Developments like mobile web services and, increasingly, intelligent devices pave the way for a more prominent role of
software related actors in the near future [13]. Applications run on platforms that allow consumers to access Internet services on their mobile devices and enable enterprises to extend their commercial applications to the mobile network [14]. Because at the moment only few platforms are developed in-house, the actors involved primarily come from the computing industry, for instance operating system and middleware vendors [15]. Consultancy firms are also relevant in the complex process of selecting and customizing application platforms. With regard to content services, various additional resources can be distinguished. Raw content needs to be created by ‘content developers’ who provide, design and produce various kinds of products or services for all kinds of end-users [14]. Raw content is typically sold on a wholesale basis to operators or providers of content and applications. There is a trend towards user-generated content (i.e. mobile web 2.0), and users can to a certain extent take over the role of the traditional content providers. However, content developers are also developing new formats based on this trend. A content provider is an actor providing and distributing content [16]. Although content providers can create their own content, they usually provide content obtained elsewhere. The UMTS forum [11] defines “content provider as a provider of services `that add value to access and transport services. Value-added services can be produced by the content provider itself or purchased from others.” While content developers and providers may focus specifically on mobile services, for many organizations the mobile channel is just another channel to distribute their content. For example, broadcasting organizations, traffic information providers, banks and tourist information offices already provide content services to customers using traditional channels like TV or the fixed Internet. Advertisers form a specific type of content providers, because they offer sponsored content. They basically provide sponsored content to content providers, aggregators and service providers, to be included in their content services, for which the advertiser pays a fee. Advertisers can also provide free (sponsored) services or content on their own. Advertisers can be any actors willing to pay for the distribution of his brand name and products and services. Advertising agencies will play an important role in delivering and possibly adapting advertisements to the mobile devices. Similar to the content providers, advertisers can focus specifically on the mobile channel or extend their marketing mix with mobile advertising. When content from a number of providers is combined in a single service offering, a content aggregator is required. Generally speaking, there are passive aggregators, who merely bundle the content, and active aggregators, who carry out filtering, editing, or customization [10, 17]. To assure the adoption of the content service, promotion and market are often required. In principal, any actor involved in the service offering can play this role. Because operators have strong brand names and large marketing budgets, it is often they that play this role.
Summarizing, we distinguish resources in four categories: those relating to networks and handsets; access to end-users and related data; applications; and content. Generally, these resources are provided by actors playing several roles, i.e. network operators, application providers, content providers, hardware manufacturers and consultancies. IV. METHOD A. Sample We collected the data through an online questionnaire between September and November 2007. To place the questions into their proper context, we asked the respondents to focus on their most important service offering or the one they were most familiar with. Finding respondents for this type of survey is a challenge, keeping in mind that there is no database with all the relevant players in the mobile services industry. Respondents were recruited using the social network of the researchers and their colleagues (35 respondents), social networking websites (10), mobile-related news magazines (1) and business presentations on the Internet (4). In addition, nine academic experts were recruited via conference papers and journal articles on mobile business models and related topics. Respondents were also asked if they knew any other potential targets in their relational network, which added another 23 respondents to out population. Fourteen anonymous respondents were recruited by a Dutch sector organization for mobile content providers. In total, 521 invitations were sent out, to which 137 people responded. The reasons provided for not taking part in the survey were lack of time, lack of expertise to answer the questions and no interest in the study. A specific group of non-respondents consisted of hardware providers and network manufacturers, who commented that they did not feel involved in mobile services, but only in technology platforms. Several academics also turned down our invitation, predominantly because they felt they had insufficient expertise to answer the detailed survey questions. To control for non-response bias, we compared the answers given by early and late respondents, and found no significant differences. Of the 137 respondents, 7 were removed, because they provided incomplete answers, and another 23 were removed who indicated that no other organizations were involved in their service offering, i.e. there were no significant resource dependencies involved. The final sample contained 97 respondents, of whom 80% came from industry, and 20 % consisted of academic and consultancy experts. Respondents are from various countries, including the Netherlands (48), Scandinavia (12), Germany (8), USA (5), Austria (6), UK (4), Italy (3), France (3), Latin-America (1), Australia (1), South-Africa (1) and other European countries (5). Our sample represents a wide variety of `most important services’, including advertising, banking, blogging, communication, e-mail, entertainment, erotic, games, health, Internet, location-based services, news, office, portal, radio, sports information, streaming, surveys, transport
information, TV, user-generated content, weather information and workforce management. Of the total number of respondents, 23 adopted the point of view of a (virtual) network operator, 14 that of an application/software provider, 20 that of a consultancy firm, 25 that of a content/service provider, publisher or content aggregator, and only 3 that of a hardware/equipment manufacturer. The organizations in our sample interact on a day-to-day basis with no (6%), one (25%), two (27%), three (18%), four (7%), five (5%) or even more (12%) organizations. B. Measures According to Pfeffer & Salancik [2], resource dependence is a product of resource importance, non-substitutability and discretion by the alter. Ideally, one would like to have a list of resources and measure the three dimensions separately. However, this leads to a repetitive, large set of questions, which appeared infeasible while pretesting the survey. Therefore, we merely survey the perceived dependence of the respondent upon the other organizations in the value network regarding each of the resources, which is consistent with the approach from Skinner et al [18] and Provan and Skinner [19]. We hypothesize that resources can be clustered into for types of access related issues, i.e. access to the network, access to the customer, access to applications and access to content. For each of these four categories, we specified several underlying resource instantiations based on the discussion in Section III, see Table I. Respondents were presented with the list of resources in the table, and were asked to rate the extent to which they felt dependent upon others for that resource, on a Likert 7-point scale (No extent – Great extent). To refine the measures, we conducted a confirmatory factor analysis (CFA), using Amos 7.0. We subsequently removed items Network_3, Customer_5 and Customer_3 from the four-factor model that load on multiple latent variables, as suggested by Anderson and Gerbing [20], based on standardized residuals and Modification Indices (MI), see Table II. While refining the measurement model, we used an imputed dataset using expectation maximization in SPSS TABLE I MEASURES Please rate the extent to which you feel you rely upon the other organizations for each of the Item resources and capabilities listed (No extent – Great extent) Network_1 Operation of mobile network Network_2 Mobile network equipment Network_3* Mobile device User_1 Billing User_2 User authentication User_3* Customer support User_4 User information (handset, location) User_5* Access to end users Application_1 Application on mobile device Application_2 Application running at service provider Content_1 Content Content_2 Marketing and promotion * Removed from final model.
15.0. We retain this measurement model and refit it with the original data. We find an acceptable model fit: χ2 (22) =29.62, p=.128; CFI=.978; TLI=.955; RMSEA=.060. To solve a Heywood case, the variance of the error term on Content_1 was fixed to 0.005 [21]. Convergent validity is acceptable, as all factor loadings for each individual indicator in its respective construct are statistically significant (p
