Effect of online personalization services on complementary firms
Introduction
Customers are often faced with complementary personalization services that are embedded in their basic services when they browse a firm’s portal or official website. For example, Apple mobile users, after receiving configuration information for an iPhone (e.g., model, color, capacity, etc.), often must select a carrier (e.g., AT&T, Sprint, T-Mobile, and Verizon, etc.) that can activate the iPhone.1 Alternatively, they might be required to search for an accessory (e.g., the manufacturer, what’s new, cases and protection, headphones and speakers, etc).2 Similarly, mobile subscribers are often bound to choose the manufacturer, color, storage capacity, operating system, etc., when they subscribe to network services.3 This example illustrates that as service qualities are extended by personalization technologies, the uncertainties of complementary demand and customers’ private knowledge of their preference and price point for online firms’ status can deteriorate.
To obtain a competitive advantage between complementary firms, it is crucial for firms to strategically offer an online personalization service that competes with its complementary firm. However, because of technical confines, product characteristics, and service differences, there is an important difference in personalization service quality; thus, online firms can offer complementary personalization services. Therefore, we allow for the asymmetry in the quality of these complementary personalization services to determine whether there are inconsistent implications.
Online personalization services, as special goods, extend beyond information goods (Wattal et al., 2009) because personalization services are usually offered free of charge by online firms. From a customer perspective, personalization services offered to customers can effectively reduce information overload and quickly capture personalized demands, thus drastically increasing customer satisfaction. From the perspective of online complementary firms, personalization services can be used to acquire customer preference information to conduct targeted advertising and price discrimination (Chellappa and Shivendu 2007). Online personalization services, can typically be achieved through embedded browser toolbars, sidebars, digital assistants, and sub-links to a website (Chellappa and Shivendu 2010). Customers, according to their preference, choose and click these toolbars or sidebars through level-by-level processing. When all sections are browsed and completed, a mobile-phone or favorite accessories webpage can be created. There are numerous examples of firms using online personalization services to interact with their customers. For example, customers use the embedded toolbars in Apple’s portal to filter information related to their personalized demands. Similarly, Amazon, Taobao, and eBay, among others, offer personalization services based on customers’ stated preferences.
In addition to the asymmetry of personalization service quality, this paper uniquely incorporates complementarity of product preferences. As in Murthi and Sarkar (2003), the impact of online personalization on a firm’s strategy can affect its key partners, for example, complementary firms. However, each firm seeks to promote its own product while retaining the ability to recommend products from multiple complementary firms. It is interesting for us to examine how each key player personalizes to strengthen its bargaining power relative to a complementary firm.
It is well known that complementarity can be used to reveal the internal compliance relationship between complementary products. However, complementarity varies among customers. We use this variable to capture customers’ product preferences. This complementary relationship frequently arises in practice, for example, in relation to smart phones and wireless networks, hardware and software, high-definition television sets and high-definition programming, and industrial products and accessories.
Synthesizing the factors illustrated above, this paper’s central focus is to investigate the implications of complementary firms offering complementary personalization services separately. Considering the asymmetry quality of offering complementary personalization services, will complementary firms implement complementary personalization services strategies? To gain competitive advantage and motivate a customer’s potential requirements, an intensely personalized service war is launched between complementary firms. A number of studies in marketing, management science, information systems, and electronic commerce have focused on the online personalization issue theoretically (Chung et al., 2009, Kwon and Kim, 2012, Mendelson and Parlaktürk, 2008, Murthi and Sarkar, 2003, Tam and Ho, 2005, Zhang, 2011). However, few theoretical works have considered how the asymmetric quality of complementary personalization services affects the pricing strategies and profits of firms in the context of E-commerce. Furthermore, there is a complementary relationship between two firms. In this paper, we address the following research questions.
Research Question 1: How does complementarity affect firms’ investments in online personalization services?
Research Question 2: What happens to equilibrium prices and profits in the presence of complementary personalization services for two firms?
Research Question 3: Under what conditions do firms find it profitable to offer complementary personalization services?
Research Question 4: Who will gain from the presentation of both basic and complementary personalization services?
In answering these questions and filling this theoretical gap, we propose a two-dimensional differentiation model of both vertical product preferences and horizontal personalization services. In this model, there are two complementary firms that sell products that are complementary to each other on a vertical dimension and that simultaneously offer two related personalization services for product attributes (e.g., by toolbars and sidebars) in their websites or online portals to interact with their customers on a horizontal dimension. Because of the difference in the capacity to offer personalization services, the two firms can offer asymmetric quality of both basic and complementary personalization services.4 We examine the following scenarios: 1) firm 1 offers only basic personalization services and firm 2 only offers complementary personalization services (“differentiated personalization services”); 2) firm 1 offers basic personalization services and low-quality complementary personalization services, and basic personalization services are infeasible for firm 2 (“asymmetric complementary personalization services”); 3) there is an asymmetric quality of basic and complementary personalization services offered by both firms (general case: “asymmetric basic and complementary personalization services”).5
Through our analysis, several new insights and findings can be obtained. We summarize the key contributions of our paper as follows: 1) we provide a model of both the vertical differentiation of product preferences and the horizontal differentiation of personalization service preferences. To the best of our knowledge, our paper is the first to simultaneously consider the effects of complementarity and the effects of online personalization services on firms’ prices and profits. 2) We introduce the concept of online personalization services and show how complementary personalization services change both firms’ pricing strategies in important ways, where the levels of personalization services are a strategic variable. Both firms can adjust the quality of personalization services to maximize their profits. In summary, the insights and results gained from the two-dimensional model contribute to the theories of complementary product pricing and online personalization.
The rest of this paper is organized as follows. We first review the related literature in the areas of online personalization, complementary product pricing, and product and service differentiation. Next, we present a two-dimensional differentiated model and define online personalization services and complementarity. We then analyze the model and derive the effects of online personalization services regarding the firms’ prices and profits in the presence of the asymmetric quality of complementary personalization services. Finally, we conclude our paper, discuss the implications for theory and practice, and present ideas for several future studies. All of the relevant proofs are provided in the appendixes.
Section snippets
Online personalization
Our paper is related to the current stream of literature on online personalization (Kazienko and Adamski, 2007, Kumar et al., 2004, Lee and Lee, 2009, Miceli et al., 2007, Vesanen and Raulas, 2006, Wang and Li, 2013, Xu and Wang, 2006, Xu et al., 2011). These studies involve information management, information technology, interactive marketing, and electronic commerce and information systems. To identify the effects of key players in the personalization process, Murthi and Sarkar (2003) provide
The model
We consider a two-market system in which there are two firms, 1 and 2, that sell products that complement each other and that simultaneously offer related personalization services for product attributes on their websites or online portals to interact with customers. The two firms are vertically located at and in a linear city. Similar to Kuksov and Lin (2010), we assume that the fixed cost has no effect on the marginal cost of production.
Analysis and results
The sequence of the game is as follows. In the first stage, both firms simultaneously determine their product prices. In the second stage, firms choose optimal levels of personalization services. We use backward induction to solve this two-stage game. First, we differentiate the profit function with respect to personalization services and obtain the equilibrium service levels in the second stage. Then, the equilibrium service levels are substituted in the profit function, and the first-order
Conclusions and discussion
In this study, we use a two-dimensional differentiation model to examine two firms that sell products that complement each other and simultaneously offer complementary personalization services online to customers. These services are offered with asymmetric quality. Given a choice between these two firms, customers evaluate the online personalization services and products of two firms to maximize surplus. In turn, both firms strategically regulate the levels of online personalization services
Limitations and future research
This is the first study that attempts to analyze the effects of complementary personalization services on firms’ prices and profits through a two-dimensional model, in which two firms sell complementary products online and simultaneously offer two related personalization services of product attributes for similar customers. However, there are some limitations of our research. Our model can be extended in the following directions. First, the current two-dimensional differentiation model does not
References (48)
- et al.
Optimal versioning in two-dimensional information product differentiation under different customer distributions
Comput. Ind. Eng.
(2013) - et al.
The privacy–personalization paradox in mHealth services acceptance of different age groups
Electron. Commer. Res. Appl.
(2016) - et al.
AdROSA—Adaptive personalization of web advertising
Inf. Sci.
(2007) - et al.
User interface features influencing overall ease of use and personalization
Inf. Manage.
(2004) - et al.
How to design personalization in a context of customer retention: Who personalizes what and to what extent?
Electron. Commer. Res. Appl.
(2012) - et al.
Psychological reactance to online recommendation services
Inf. Manage.
(2009) - et al.
Customizing customization: a conceptual framework for interactive personalization
J. Interact. Mark.
(2007) - et al.
A Stackelberg model of pricing of complementary goods under information asymmetry
Int. J. Prod. Econ.
(2011) - et al.
Multi-agent technology and ontologies to support personalization in B2C E-Commerce
Electron. Commer. Res. Appl.
(2014) - et al.
Building bridges for personalization: a process model for marketing
J. Interact. Mark.
(2006)
Testing the moderating effects of toolkits and user communities in personalization: the case of social networking service
Decis. Support Syst.
Intelligent agent supported personalization for virtual learning environments
Decis. Support Syst.
The personalization privacy paradox: An exploratory study of decision making process for location-aware marketing
Decis. Support Syst.
A bertrand model of pricing of complementary goods under information asymmetry
J. Bus. Res.
The moderating role of commitment on the spillover effect of marketing communications
J. Mark. Res.
Leadtime-Variety Tradeoff in Product Differentiation
Manuf. Serv. Oper. Manage.
Selling and leasing strategies for durable goods with complementary products
Manage. Sci.
Product differentiation and capacity cost interaction in time and price sensitive markets
Manuf. Serv. Oper. Manage.
Exclusive channels and revenue sharing in a complementary goods market
Mark. Sci.
A model of advertiser—portal contracts: Personalization strategies under privacy concerns
Inf. Technol. Manage.
An economic model of privacy: A property rights approach to regulatory choices for online personalization
J. Manage. Inf. Syst.
Mechanism design for “Free” but “No Free Disposal” services: the economics of personalization under privacy concerns
Manage. Sci.
My mobile music: an adaptive personalization system for digital audio players
Mark. Sci.
Product differentiation and collusion sustainability when collusion is costly
Mark. Sci.
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