Business Strategy For Managerial Economics: Analysing Mobile Service Providers

Describing the issues

Discuss about the case study Business Strategy for Managerial Economics.

This project analyses a business strategy of a mobile service provider. With technological improvement day by day, competition in product market is growing. To keep parity with the current trends, mobile service providers adopt various strategies. There are both advantages and disadvantages of the strategies. Application of Game theory helps to analyse the issues effectively. According to Game theory in market framework, another firm (Manshaei et al. 2013) follows every firm’s strategy. Therefore, in formulating strategies, every company needs to consider competitor’s strategy simultaneously. One strategy in competitive market environment of mobile service is using bundling technique. The mobile service provider can provide more than one service in a package to gain competitive advantage over its competitors. A company can use price bundling strategy. In this case, the company can sell multiple services in a portfolio for a lower price than that could be charged for individual selling. These theories are used to analyse the case study.

Issue highlighted in this assignment is that what would be possible strategy of the mobile operators in order to increase profit in spite of falling mobile prices. There are multiple options available to the mobile operators. For the service providers, mobile price falling is a matter of concern. As price falls, demand for services increase overtime. Therefore, to deal with this problem, companies offer unlimited voice call service along with free SMS service. This is a strategy of service bundling. This strategy is not enough to compete in the market. Hence, more strategies need to develop for the mobile operator.

This is a market of oligopoly, where a few companies operate to provide mobile services. In this market new firms can enter in the market if they have potentiality. In oligopoly market companies can share the total market among them. Direct engagement in price war may result in loss for all the operators (Myerson 2013). One of the main problems that are faced by the mobile operator is rising capacity demand. They need to investment in developing mobile networking. Now the problem is whether all the firms behave rationally or not. Capacity improvement must have some costs such as network maintenance, marketing, technology development etc. If all mobile operators form a cartel, they can maximize industry profit and individual profit. However, the success depends on rationality of the individual firm. If one firm betrays, the cartel may break down (Rapoport 2012). 

Approaches for mobile operator

The factors affect the demand for mobile services are accessibility of the network services by consumers, different choices of consumers for broadband services etc. As attractive packages are offered by mobile operators, demand for mobile data plan services are rising. Due to acquire more profit, companies try to offer more data plan. Increasing supply reduces the price of mobile plan. As there are multiple mobile operators in the market, market is shared among them. Therefore profit margin tends to fall (Manshaei et al. 2013).

Figure 1: Demand and supply of mobile data plan

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Approaches for mobile operator

Figure 2: Different approaches for mobile operators

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Bundling theory

Bundling technique is strategy, which is applied by different organizations. Company can use service bundling or price bundling. In service bundling, mobile operator company can choose to offer various services as a package. Value added service or cross selling may also be done. This strategy attracts more customers. This strategy is mainly followed in special season. Price bundling is more attractive to the customer. It offers the package of variety services at much lower price than the consumer might have bought those services individually. Bundling strategy is profitable if marginal cost of using this strategy is low (Chung et al. 2013).

Game theory

Game theory is a model, which depicts market strategy of several existing competitors in the market. It is a useful tool in decision making. Using game theory, one mobile operator can choose strategy after consider other operators strategy in business operation. Nash equilibrium in game theory can be achieved if there is a dominant strategy for each company. Once the company reaches at Nash equilibrium, it would not want to deviate from the chosen strategy. The strategy achieved at Nash equilibrium I optimal solution for the mobile operator. This solution gives best possible utility given opponent’s decision (Derdenger et al. 2013).

In game theory, the mobile operators are said to be rational if they try to maximize their own payoff with the available information. If all players behave rationally to maximize their profit, the decision making would be easier. In order to forming a strategy in game theory, first step is to identify the game element. The mobile operators can choose price, service, cost or capacity improvement in plying game (Kang et al. 2012). If there is imperfect information available to the operators regarding other companies, the game may be continued for several steps to reach equilibrium. The information required for a mobile operating company is performance of Competitor Company in the industry, pricing strategy, marketing strategy, financial performance etc (Trestian et al. 2012).

Describing different approaches

Strategies available to the mobile operators are as follows:

Figure 3: Profit maximization strategies by mobile operator

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Possible solutions of the identified problems can be presented as below. Bundling strategy in game theory for mobile operators in order to increasing profit is as follows:

Figure 4: Bundling strategies

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If the mobile operators choose to use bundling techniques, they have options represented in the above table. If the mobile operator chooses to provide multiple service packages, they can offer it at lower price. There is no package available for single service. To increase revenue, the firm can sell single service at higher price. Selling single service at lower price cannot generate much profit. However, in competitive environment it is good policy (Shi et al. 2012). However, this strategy may not be effective. If one firm charges low price for single service, other firm may follow this operator and tend to reduce price of any service. Direct engagement in price war would benefit no firm. Continuous reduction in price would reduce both industry and individual profit. Therefore, offering single service at low price is not a useful strategy for the mobile operator.

In order to maximize revenue, the mobile operators can offer multiple services at high price. For the success of this strategy, it is required to take strategy evenly by all firms. It can be done by forming cartel. Cartel can be formed among several mobile operators by negotiating among themselves. If cartel can be formed, all the mobile operators can act as a monopolist in the market. Combined strategy would be to sell single or multiple services at higher price without government regulation (Stucchi et al. 2012).

If there is no government intervention, mobile operators can charge price freely. They can set price like a monopolist. They can charge uniform rate for data plan. The charge would be higher. The quantity of service is determined at the point where MR intersects the marginal cost curve. When they act independently, they charge price according to the equilibrium point of intersection, which is lower than monopoly price. As they act like a monopolist, they charge price according to average revenue, which is higher than competitive price. At this price, mobile operator can provide service at higher price. The can make sufficient profit, as the consumer have no other options than to buy service at higher price. They cannot find any other alternative options in the market. There is a chance to maximize industry profit.

Bundling theory

Figure 5: Pricing strategy of Cartel

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They can offer single service at higher price. In this case also consumers are compelled to avail service. The profit of the individual firm depends on marginal cost of production. If the cost of production is high, that firm would make less profit compared to other firm.

This strategy would be successful if all operators behave rationally. If any firm thinks that, it will charge lower price than cartel charge, at short run, it can make huge profit as consumers will move to the firm, which charging lower price. Nevertheless, in long run, this policy cannot sustain. In game theory, irrational actions are chosen by firm; if it thinks that its action would not followed by other firms. This perception is wrong in competitive market. When other firms realize that one firm is behaving otherwise, they start to play independently and try to take random strategy (Katsoulacos and Ulph 2013). If other existing mobile operators tend to reduce price of data plan, this would break down the cartel. In the price conflict, when the price is down below firm’s individual marginal cost, nothing but loss occurs. Therefore, trust is primary criteria for success of cartel. If strategies of two firms are considered the pay off matrix can be as follows:1^st mover

Figure 6: Pay off matrix

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In the above pay off matrix, different strategies of profit maximizations are shown. If it is assumed that the mobile operators have chosen three strategies such as minimization of cost, capacity maximization and collusion. The analysis is made for two rival mobile operators in the market. One company is first mover, which chooses decision first. At the time of taking strategies, the first mover takes decision of other firm into consideration. It is also assumed that both the mobile operator behave rationally.

If the first mover thinks that 2^nd firm may chose to minimize cost in order to the competitive advantage, the best available strategy for 1^st firm is capacity maximization. It may happen that the first firm incurs higher cost compared to 2^nd mover to provide lucrative data plan services or unlimited phone cal services. In this case, to get competitive advantage over the competitors, it would be strategic to improve capacity. Improvement in data plan, network services, reduction in call drop etc can give first firm a competitive advantage. This strategy would give first firm highest payoff. If both the firm chooses cost reduction strategy, this would give same utility to both the firms. Collusion cannot be formed without consent of other mobile operator; hence, this strategy would give nothing to the first firm. If the second firm chooses to maximize capacity, the first firm would definitely choose maximize capacity, as this would give both the mobile operator equal pay off. It is the optimal strategy for first firm. 

Game theory

If the strategy of second firm is to make collusion with first firm, the first firm has two options. One is to agree with the first firm and make the cartel, which gives both the mobile operator highest payoff. Another is making decision independently and choosing capacity maximization strategies. In the latter case, the first firm gets maximum profit and second firm gets nothing. This decision depends on the objective of the firm. If the first mobile operator does not rely on cartel o does not have trust on second mobile operator, it may choose to maximize capacity. Capacity maximization would be optimal solution as it is profitable in long run. If firm can invest in improving mobile services and capacity improvement, it may get cost advantage in future for the expansion of business.

Capacity maximization strategy gives the first mover dominant strategy. It is the optimal strategy for the first mover mobile operator. Even if both the firm takes simultaneous decision to maximize payoff, the Nash equilibrium would be the payoff 5 for both the firm. This will benefit both the firm.

Therefore, it can be inferred that for all the mobile operators, capacity maximization along with bundling technique would be optimal solution.

Conclusion

The project analyses the optimal strategy of the mobile operators, who suffer from falling mobile plan price. With increasing demand for data plan and other services such as unlimited free call or SMS service. By providing such benefits to the consumers cannot make sufficient profit in long run. Low price discourages the mobile operator to provide service in long run. Therefore, it would be optimal to take decision for capacity improvement, which can help the mobile operator to provide better service in the market in long term.

References

Chung, H.L., Lin, Y.S. and Hu, J.L., 2013. Bundling strategy and product differentiation. Journal of Economics, 108(3), pp.207-229.

Derdenger, T. and Kumar, V., 2013. The dynamic effects of bundling as a product strategy. Marketing Science, 32(6), pp.827-859.

Kang, X., Zhang, R. and Motani, M., 2012. Price-based resource allocation for spectrum-sharing femtocell networks: A stackelberg game approach.IEEE Journal on Selected areas in Communications, 30(3), pp.538-549.

Katsoulacos, Y. and Ulph, D., 2013. Antitrust penalties and the implications of empirical evidence on cartel overcharges. The Economic Journal,123(572), pp.F558-F581.

Manshaei, M.H., Zhu, Q., Alpcan, T., BacÅŸar, T. and Hubaux, J.P., 2013. Game theory meets network security and privacy. ACM Computing Surveys (CSUR), 45(3), p.25.

Myerson, R.B., 2013. Game theory. Harvard university press.

Rapoport, A. ed., 2012. Game theory as a theory of conflict resolution (Vol. 2). Springer Science & Business Media.

Shi, H.Y., Wang, W.L., Kwok, N.M. and Chen, S.Y., 2012. Game theory for wireless sensor networks: a survey. Sensors, 12(7), pp.9055-9097.

Stucchi, T., 2012. Emerging market firms’ acquisitions in advanced markets: Matching strategy with resource-, institution-and industry-based antecedents.European Management Journal, 30(3), pp.278-289.

Trestian, R., Ormond, O. and Muntean, G.M., 2012. Game theory-based network selection: Solutions and challenges. IEEE Communications surveys & tutorials, 14(4), pp.1212-1231.