This research seeks to further our understanding on the economic challenges in network industries. Although the economics of network markets like telecommunications, Internet, and service operations in banking, legal and airline industries have become a major field of economic research; knowledge about how to manage innovation within these markets is less advanced (HOBDAY et al. 2000: 793; CHESBROUGH 2003: 198). The goods and services of these industries regularly present themselves as complex system products, which are composed of multiple mutually dependent components and often supplied by different industries (HOBDAY 1998: 691; TIDD 1995: 308).
(Au and Kauffman, 2008) the mobile payment industry has a bright future throughout the world, but there will be many challenges ahead. However the actors of mobile payment network influenced by external factors such as social and societal opinions and values, economic factors related to the society in which the business system is operating, political actors and decisions that affect the business system, technological developments that can be deployed in the payment system, ecological issues and concerns, and legal issues and boundaries (Arvdisson ,2012 )
Dahlberg et al. (2008) find that, the business value of mobile payment services and the roles of the players in the mobile payments service markets are unclear the organization of the mobile payment services value chain has a significant role in the development of mobile payment services. As long as the roles of key players are unclear, mobile payment services will proceed at a slow pace (Au and Kauffman, 2008) Economic analysis offers the potential to understand a variety of mobile payment related phenomena on the basis of electronic payment initiatives of the past, as well as on the basis of other technologies that give rise to similar issues for their key stakeholders. Economic theory offers useful ways to understand and interpret past developments, and predict what is likely to happen in the area of mobile payments in the coming years.
Arvdisson (2012 )identified preliminary critical concerns based on the understanding of a cashless society, is to provide unique value for different types of customers is critical; to offers this value should be ability to combine scale economies in production and operations. And, it must be done through collaboration with other actors as well as with the consumers.
The performance of firms in many industries from banking to telecommunications to social networks depends on their offering of products that exhibit network effects. A product exhibits network effects if its value to users depends not only on benefits from the product itself but also on access to the network of people using that product or a compatible one (Katz and Shapiro, 1985, 1992; Farrell and Saloner, 1986; Liebowitz and Margolis, 1994; Economides, 1996; Sheremata,2004).
Network externalities, will play a big role in creating value in m-payments systems. The more merchants there are who accept m-payments, the more consumers will be willing to use them. This can only happen, however, if there is an organized set of technology standards that every merchant and consumer can trust. Without integrated and universal standards, the m-payment industry and the markets in will remain relatively fragmented and localized, forcing merchants as well as consumers to accept several different m-payment systems and preventing providers from reaching the critical mass needed to survive or deliver the best services to consumers. To achieve the objective of having common standards, however-payment technology and service providers from different industries must join forces. (Au and Kauffman, 2008)
The collapse of Simpy, an alliance of major European mobile network operators, offers a good lesson on the need for cross-industry collaboration; to date, however, there are few initiatives to match Simpy in the US, where the market is much more fragmented among mobile network operators in comparison with Europe, Japan and South Korea (Au and Kauffman, 2008)
In the framework proposed we define a network as a group of firms connected to each other through collaboration alliances. The advantages to entering into a network range from the direct benefits obtained from entering into an alliance to the indirect benefits from being part of the network. Direct benefits may take the form of access to knowledge resources, competencies, and cost economies. On the other hand, indirect benefits generally refer to greater access to information flows and control benefits from being strategically positioned in the network.
2. Literature Review
In network industries the market mechanism of demand and supply is not working properly because of existence of network externality. Network externality in economic concept is the increase in a product or service utility because of extending its customer network or technological network (Shy 2004). This effect could cause formation of monopolies and it is important to control it (Brennan 2009).In science the term network industry might be used to refer to telecommunication and computing industries or to the network of organizations, which are working together to produce a product or to deliver a service. Here, network industry is used to define a particular sub-set of the economic definition for network industries.
The consideration is network industries with a physical infra-structure in which the companies are interconnected. The infra-structure in network industries is a shared resource, which should be maintained, expanded, and structured (K??nneke and Finger 2009).to achieve this goal requires the governance body to have a foundation for collaboration and analyzing the impact of their strategies and policies.
In network industries it is important for companies to collaborate to utilize the resources in a more effective way, but these collaborations create barrier for new companies and therefore ineffectiveness (Lin 2005; Gayle 2006). For this reason, it is necessary to explore the dynamics of competition and collaboration in the mobile payment system as a network industry. Network externality theory applied in the contexts of interorganizational systems, digital wireless phones, and electronic banking and ATM networks, among others. (Au and Kauffman, 2008)
The network industry in economic related to interconnected markets which characteristics is: (1) consumption externalities, (2) importance of compatibility and standards, (3) switching costs and lock-in, and (4) the significant economies of scale in production (Shy 2004). Because of existence of these characteristics the invisible hand of demand and supply is not working properly in these markets. According to Katz and Shapiro they highlighted the role of externality on competitions in network markets. They came out of three types of externalities: (1) indirect consumption externalities, (2) direct consumption externality, (3) and externality for durable products. In all of these cases the utility of the product for a customer increases with the number of other customers which use the same product. Therefore, the competitors in this market can increase their market share using compatibility as one of the influences to attract the customers. (Katz and Shapiro 1985).
This effect can change the way competitor make strategic changes in the market. For example the select of open-source code by Sun Microsystems can be explained by this network effect. (Garud and Kumaraswamy ,1993)pinpointed this complexity in strategies in network industries which arose because of network effect. In telecommunication industry this monopolistic opportunity is studied by Gabel. As he puts it AT&T was able to monopolies the United States telecom industry because of its first-mover advantage and its access to the infrastructure that prevented the new entrants from the market. Therefore, the dominant strategy in the network industries is to build a higher quality network to dominate the rivals (Gabel 1994).
Not one single bank or mobile network operator covers the whole market share, so there is a need for cooperation and collaboration. Collaboration between mobile network operators may not be obvious as they are very competitive on their core voice and data business. Collaboration with banks may not be obvious as parties have different business objectives, different perspectives on revenue sharing, and different mind sets (mobile operators are more agile, banks focus on robustness). Our role as researchers is to objectively examine and study the unexplored research area; how the collaboration situation in the mobile payment industry gives rise to different commercialization alternatives for mobile payment solutions. This is since we believe that it is hard for an actor in the mobile payment industry to develop, produce, market, sale and deliver a mobile payment product or solution to the market alone. Collaborations hence become essential to the value network and are therefore interesting to investigate further.
3. Theory: Networks and network industries
In conventional terms empirical examples of network industries embrace electricity supply, telecommunications, and railroads. Network industries can be defined as those where the firm or its product consists of many interconnected nodes, where a node is a unit of the firm , organization or its product, and where the connections among the nodes define the character of business in the industry. (Gottinger, 2005)
The nodes of these industries are units like electricity lines, phone sets, computers, and information platforms. The number of nodes and connected consumers may grow in tandem, but a distinction exists between an additional node on the network and an additional consumer. (Gottinger, 2005)
Economies of scale have been given as a reason for maintaining monopoly in industries that require heavy sunk costs. If more than one firm provides the same service, sub additively is said to occur. This concept implies that costs of supplying a certain level of output would be higher when two or more firms operate in the market as opposed to one (Baumol et al., 1982).
Besides the supply-side economies of scale the demand-side economies of scale are commonly seen in the communications and computer industries among others. For some goods and services, a person’s demand depends on the demands of other people, or the number of other people who have purchased the same good may affect a person’s demand. For example, the buyer of a telephone or fax machine would have not bought it if there were no one else who had purchased or would have purchased it. When more people have purchased it the more value of a telephone or fax machine the buyer would have obtained. This is a positive network externality based on an ‘actual’ or ‘physical’ network
Network effects directly challenge an important principle of classical economic theory, which posits decreasing (and eventually negative) returns to scale in most markets. Also this theory basically deals with increasing returns problems in case of supply-side economies of scale but ignores cases of demand-side economies of scale brought about by increasing value of existing users through increased demand, that is, through network externalities.
That is, network markets offer increasing returns over a large portion of the demand curve or even the entire demand curve. Markets with increasing returns imply that bigger is better and consumers deriving more value as the number of consumers grows. On the other side of this situation in terms of market structure is that the strong grow stronger and the weak become weaker.
3.1 Returns to scale
From the traditional economics perspective, returns to scale (RTS) are a characteristic of a particular production technology or production function. They describe the impact on output of scaling all inputs up or down in constant proportions.
Increasing RTS refers to a more than proportional change in output for a given change in inputs, diminishing RTS refers to a less than proportional change in output for a given change in inputs, and constant RTS refers to a proportional change in output for a given change in inputs. In most instances, one would expect to see constant RTS, decreasing RTS are typically a short run phenomenon caused by one input being held fixed, and increasing RTS are sometimes possible because an increase in output does not require an increase in fixed costs. It is also possible for a technology to have RTS vary with levels of output and other factors (Varian, 1996).
Economies/diseconomies of scale, is a related concept but is a characteristic of a particular cost function. This concept describes the impact on total costs of scaling output up or down. Economies of scale refers to a less than proportional change in total cost for a given change in output, and diseconomies of scale refers to a more than proportional change in total cost for a given change in output. If costs go up proportionally with a change in output, neither economies nor diseconomies of scale exist.
”Koontz (1951) was the first to introduce a distinction between economies of size and of density” (Antoniou, 1991), but ”after Caves et al. (1984), it became customary to analyze transport industry structure using two indices: (1) economies of density (RTD) and (2) economies of scale with variable network size (RTS)” (Basso and Jara-Diaz, 2006a,b). RTD was defined as the impact of increasing output while holding network size, average length of haul, and load factor constant, and the definition of economies of scale in the transportation industry was adjusted to describe the impact on cost of changing both output and network size simultaneously and by the same percentage. Neither of these definitions coincides with the economic definition of economies of scale due to the inclusion of operating characteristics in the cost function. The traditional economic definition of economies of scale describes the impact on cost of increasing output while keeping input prices constant, and with management making decisions that result in the maximum profit. This entails adjusting or holding constant things such as load factor, network size, and average length of haul as appropriate. By including these network factors as control variables in a cost function, it is only possible to see the impact of increasing or decreasing output while holding all other independent variables constant or adjusting some simultaneously and by the same percentage and holding the others constant. Again, the traditional economic definition of RTS involves the impact on cost of increasing output, while holding the cost of inputs constant, and allowing all other factors to vary in the most efficient manner in order for the individual firm to maximize profits.
3.2 Social capital Theory
This paper links Social capital network constructs to network-related value creation and capture, and to competitive advantage. In doing so, it potentially contributes to clarifying the elusive but important connection between Social capital network and firm value. Network externalities are strategic resources (Shankar and Bayus, 2003). Studying how network members or providers derive value from networks can help us identify where strategic resources create and how they translate into economic rents.
A related theory on the significance of networking focuses on the value of networking and collaboration in creating social capital. Social capital contains three main elements:
(1) Resources embedded in a social context;
(2) That are accessed or mobilized;
(3) In purposive action (Lin, 1999, p. 30).
The value of networking in this perspective is seen as lying in its ability to harness resources held by other actors and increase the flow of information in a network. Furthermore, a network can apply more influence on its social and political surroundings than individual actors (Lin, 1999). According to Hargreaves (2004), Social capital can also help spread innovation and that through bottom-up networks that can both quickly link the nodes to innovators and may themselves lead to innovations that are more open to change and challenge and less likely to ossify than top-down strategies.
Knowledge lies in both individual and collective and therefore networks are needed to increase effectiveness. The value of networking lies in spanning ”structural holes” where information or skills are lacking (Burt, 1992).This creates collaboration a potentially successful strategy for all actors involved in a network, as each may in theory be able to extent structural holes, something which becomes more likely when a network consists of several actors. In this Perspective, networking can be failed because of the strong an imbalance between actors in terms of what information/skills they possess or where structural ties can imprison actors in negative behavior patterns (Borgatti & Foster, 2003).
Social capital may itself lie in the extent to which firms are experienced at working with others. There is evidence from the business field that firms with more of this experience are likely to form more interorganisational networks (Brass et al., 2004).
Collaborations in this perspective are more strongly driven by clearly worked out self-interest than in the constructivist model. The goals of networking from this perspective would lie mainly in knowledge transfer or the acquisition of increased influence or voice within Mobile payments Network. Where the goal is the former, Mobile payments Network are likely to be working together because of perceived different strengths and weaknesses and may develop specialisms further through collaboration, such as offering services to their consumers of different actors that have capacity in that area. Full-service extended Mobile payment actor, where actors team up with other providers to offer services they cannot provide on their own, may in many cases be another example of this model.
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