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Essay: Switching Costs

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Free Marketing Essay | Switching Costs

Switching Costs

Switching costs are a key focus of many firms, both from the point of view of costs incurred when switching suppliers or systems, and in markets in which consumers have costs of switching between competing firms’ products. In a market with switching costs , a firm’s current market share is art important determinant of its future profitability Klemperer (1995) examines how the firm’s choice between setting a low price to capture market share, and setting a high price to harvest profits by exploiting its current locked-in customers, is affected by the threat of new entry, interest rates, exchange rate expectations, the state of the business cycle. This work, along with his discussion of switching costs, introductory offers and price wars, offers some insight into the double edged nature of switching costs, however a more detailed analysis of the costs of switching, and the psychological effects on customers, is needed in order to gain a fuller understanding of the phenomenon.

Murrow and Nowak (2005) show that the cost of switching can explain an additional 30% of the variation affiliated with the intent of a consumer to stay or leave an existing supplier. In their analysis, they focused on the costs to nurses of switching jobs, claiming that: "Switching costs can be thought of as barriers to exiting for employees, just as they are barriers to changing a consumer’s supplier." There is, however, more data available on consumer switching costs as these costs have been recognized by administrators as being significant for the last couple of decades. Several supplier switching costs for consumers were identified by Murrow and Nowak (2005) that seemed to be most responsible for the decision making process: economic risk, evaluation costs, learning costs, setup costs, benefit loss, direct money costs, personal relationship loss, and associative loss. Examining these factors reveals that many of them are psychological, for example: the magnitude of economic risk is often influenced by an individual’s perception, and learning costs are often seen in a time based context. There is also cognitive dissonance associated with any personal relationship, or associative loss. Indeed, Murrow and Nowak (2005) concluded that the psychological implications of turnover are often neglected or diminished but they are significant factors in the decision to change employment.

About 60% of "satisfied" customers reportedly leave their present supplier. The Forum Corporation (Boston, MA) analyzed 14 major firms and examined why that occurs, finding that 15% of customers left because they found a better supplier, 15% found a less expensive supplier, and 70% left because of poor or little attention provided by the supplier. Of these, only finding a better or cheaper supplier can be seen as a cohesive reason: leaving because of lack of attention, with no superior replacement option, can be perceived as a psychological factor. It is thus interesting, and significant, to note that the psychological factors have more than double the importance of the cohesive factors.

Winning the market-share battle for industry leadership is not always synonymous with high profits. Indeed, it has been shown that gains in market share attained through excessive expenditures, below-cost pricing, or inappropriate mergers and acquisitions can be destructive to financial health. (Armstrong and Collopy, 1996; Buzzell Gale and Sultan, 1975 and Zeithaml and Fry, 1984) Nonetheless, other things being equal, market-share leadership, which is synonymous with industry leadership, can indeed be conducive to a healthy bottom line. (Scherer and Ross, 1990) Firms, like Microsoft, that possess a strong market share or customer base in a given period, will have a significant advantage over rivals with a smaller customer base in ensuing periods because of scale and scope effects, customer inertia, and switching costs. For example, Microsoft can spread the half-billion dollar cost of developing a new version of its Windows operating system over its 200 million user base, effectively lowering the unit cost of development to about two dollars. For other products, consumer inertia and perceived inconvenience, as opposed to explicit time or money costs, inhibits buyers from switching. In either case, switching costs clearly work to the advantage of firms with strong market positions. (Smith, Ferrier and Grimm, 2001)

This appears to indicate that a firm is often best placed to use switching costs, and customer lock-in when it is in a dominant position in its market, and thus has power over its buyers. Even perceived power, such as that possessed by Microsoft, can work in their favour: there are many viable alternatives to Microsoft products available, but many people buy Microsoft as they believe there are no other options, or that to use an alternative would either require them to learn new skills, or produce work that would be incompatible with the dominant systems being used by their peers. (CNN, 2002)

The results from a series of multiple regression analyses (Patterson and Smith, 2003) show switching costs capture a substantial amount of the explained variance in the dependent variable, propensity to stay with a focal service provider. Furthermore it has been demonstrated, using interaction terms, that these switching costs appear to be universal across west-east cultures. However, significant variations were found across industries, with high technology industries, such as computing, more able to lock customers in than low tech ones, such as food manufacturers. The differences across these industries can be explained by the perceived differences in their products: in theory there is no physical difference between choosing a cheaper operating system and choosing a cheaper type of bread. However, many consumers are unfamiliar with the intricate workings of a computer, and believe that if they chose a cheaper option by a less well known company they would be left with a product they would have trouble using, and may be left with no after sales support. In contrast, people readily recognise the similarity between different types of bread, and are thus more comfortable choosing a cheaper, or healthier, option.

Equally, high-technology markets represent unique problems for organizational buyers and, in turn, for their existing and potential vendors. These problems are due to high levels of uncertainty and the presence of switching costs tied to existing technologies or vendors. Heide and Weiss (1995) focused on two aspects of buyer decision making in such markets: whether buyers include new vendors at the consideration stage of the process and whether they switch to new vendors at the choice stage. Using survey data from organizational buyers’ purchases of computer workstation equipment, they presented a joint test of the antecedent conditions that influence the two processes, and based on a sequential logit model, they show that individual antecedents have different effects on consideration and switching behavior.

It has been shown that buyer switching costs may arise as a result of prior commitments, both to a technology and to a particular vendor (Jackson 1985). With respect to the former, previous studies of technological products, such as computer equipment, have shown that organizational buyers frequently purchase such products from existing vendors, who may have provided an earlier version of the product in question. (Rosenthal 1984) As a result of the prior purchases, buyers may have invested in assets that are incompatible with new products. For example, computer software is frequently idiosyncratic to a particular system and cannot be easily adapted to a new one.

In addition to compatibility problems, buyers may face switching costs because of established relationships with particular vendors. For example, buyers may have developed routines and procedures for dealing with a specific vendor that will need to be modified if a new relationship is established (Heide and John 1990). In some situations, an entire set of working relationships will need to be established with different parts of the vendor’s organization, such as with technical support personnel and application specialists.

The general effect of both types of switching costs for a buyer is a disincentive to explore new vendors (Jackson 1985). All else being equal, buyers will be motivated to stay in existing relationships to economize on switching costs. Specifically, we expect the presence of both types of switching costs to reduce the likelihood that an open consideration set will be used. In cost-benefit terms, the potential benefits associated with identifying new vendors may not justify the information acquisition costs involved. Furthermore, in situations in which an open consideration set is maintained, we predict that the presence of switching costs will increase the likelihood that an existing vendor will actually be chosen. Under such conditions, switching to a new vendor would require the buyer to actually incur the costs of switching.

The above discussion should fully support the view that the use of switching costs, and aggressive lock in, are most effective when used against large scale corporate buyers. However, one of the main problems with pursuing a stratey of aggrssive lock in is that previous predictions are not entirely clear cut. Essentially, switching costs constitute a form of dependence that may prompt buyers to deliberately pursue dependence-balancing strategies (Heide and John 1988). Maintaining an open consideration set or exploring new vendors may be one such strategy. In spite of this, it is generally accepted that these types of switching costs represent a constraint on a buyer’s exploration of new vendors (Jackson 1985).

Finally, Zauberman’s (2003) article examines how dynamic changes in information cost structure and time preferences affect consumers’ search and switching behavior over time and lead to lock-in. Experiment 1 shows that a small initial investment is sufficient to produce lock-in. Experiment 2 shows that the results of a prior investment on lock-in are not due to psychological commitment but to a shift in relative costs of incumbent and new options. Experiment 3 shows that respondents fail to anticipate how their prior investment will lock them in.

The above analysis produces no clear cut conclusions as to when aggressive lock in is preferable. In general, it appears to be best when the industry is complex, and poorly understood by consumers, when the firm has a dominant marketing position, or when consumers are purchasing on such a scale that they are naturally incurring switching costs, such as corporate consumers. However, the first two of these can always produce a consumerism backlash, and the third can often be overcome by a firm that is determined to streamline its costs and break through the lock in.

In conclusion, switching costs will always have the potential to cut both ways for the firm that uses them, and there are no clear cut predictions, merely guidelines. An aggressive lock in strategy remains one of the most potent ways for firms to secure their profit margins for the forseeable future, but even the most successful of these can and will eventually be challenged, by the market forces, as is now happening to Microsoft, once the most successful of all firms pursuing this strategy. (CNN, 2002)

References

. Armstrong, J. S. and Collopy, F. (1996) Competitor orientation: Effects of objectives and information on managerial decisions and profitability. Journal of Marketing Research, May, p. 188.

. Buzzell, R. Gale, B. and Sultan, G. (1975) Market share–a key to profitability. Harvard Business Review, Jan-Feb, p. 97.

. CNN (May 17, 2002) Sun touts StarOffice as affordable alternative. http://archives.cnn.com/2002/TECH/ptech/05/17/sun.staroffice.idg/index.html

. Heide, J. B. and George John (1988), The Role of Dependence Balancing in Safeguarding Transaction-Specific Assets in Conventional Channels. Journal of Marketing; Issue. 52, p. 20.

. Heide, Jan B. and George John (1990), Alliances in Industrial Purchasing: The Determinants of Joint Action in Buyer-Supplier Relationships. Journal of Marketing Research; Issue 27. p. 24.

. Heide, J. B. and Weiss, A. M. (1995) Vendor consideration and switching behavior for buyers in high-technology markets. Journal of Marketing; Vol. 59, Issue 3, p. 30.

Jackson, B. B. (1985), Winning and Keeping Industrial Customers. Lexington, MA: Lexington Books.

. Klemperer, P. (1995) Competition when Consumers have Switching Costs: An Overview with Applications to Industrial Organization, Macroeconomics, and International Trade. Review of Economic Studies; Vol. 62 Issue 213, p. 515.

. Murrow, J. and Nowak, P. (2005) What Nurses Want. Marketing Health Services; Vol. 25 Issue 1, p. 25.

. Patterson, P. G. and Smith, T. (2003) A cross-cultural study of switching barriers and propensity to stay with service providers. Journal of Retailing; Vol. 79, Issue 2, p. 107. Rosenthal, S. R. (1984), Progress Toward the ‘Factory of the Future. Journal of Operations Management; Issue 4. p. 203.

. Smith, K. G. Ferrier, W. J. and Grimm, C. M. (2001) King of the hill: Dethroning the industry leader. Academy of Management Executive; Vol. 15, Issue 2, p. 59.

. Zauberman, G. (2003) The Intertemporal Dynamics of Consumer Lock-In. Journal of Consumer Research; Vol. 30, Issue 3, p. 405 .

. Zeithaml, C. and Fry, L. (1984) Contextual and strategic differences among mature businesses in four dynamic performance situations. Academy of Management Journal, Issue 27, p. 841.

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