Evaluating strategies for promoting retail mobile channel using a hidden Markov model |
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| Institution: | 1. Sam M. Walton College of Business, University of Arkansas, United States;2. Management (Emeritus), Marketing and Quantitative Methods, Johnson Graduate School of Management, Johnson College of Business, Cornell University, United States;1. DePaul University, Driehaus College of Business, 1 E. Jackson Blvd., Chicago, IL 60604, United States;2. University of Zagreb, Faculty of Economics & Business Zagreb, Trg J. F. Kennedyja 6, 10000 Zagreb, Croatia;3. Northwestern University, Medill School of Journalism, Media, Integrated Marketing Communications, 1845 Sheridan Road, Evanston, IL 60208, United States;4. Keio University, Graduate School of Business Administration, 4-1-1 Hiyoshi, Kohoku, Yokohama 2238526, Japan;1. Department of Management and Marketing, Saginaw Valley State University, University Center, MI 48710;2. Department of Marketing and Supply Chain Management, The University of Memphis, Memphis, TN 38152;3. Department of Marketing, Darla Moore School of Business, University of South Carolina, Columbia, SC 29208;4. Department of Marketing, Wayne State University, 2771 Woodward Ave, Detroit, MI 48201;1. Management & Marketing Department, John L. Grove College of Business, Shippensburg University;2. Area of Marketing and Supply Chain Management, Rawls College of Business, Texas Tech University, 703 Flint Avenue, MS 2101, Lubbock, TX, 79409;1. University of Edinburgh, Business School, Edinburgh, United Kingdom;2. University of Southampton, Southampton Business School, Southampton, United Kingdom;3. University of Central Florida, College of Business, Orlando, United States;1. Neeley School of Business, Texas Christian University, TCU Box 298530, Fort Worth, TX, 76129, USA;2. Smeal College of Business, The Pennsylvania State University, 455 Business Building, University Park, PA, 16802, USA |
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| Abstract: | With the proliferation of mobile communication technology, many firms, including retailers and consumer banks, are making efforts to develop mobile platforms to better engage with their customers and reduce operational costs. However, the cost advantage of these mobile technologies will not yield fruition unless the mobile channel accounts for a significant share of total transactions. In this article, we explore potential options for firms to promote usage of the mobile channel. To achieve this, we propose a hidden Markov model to both model customers’ decisions and assess different managerial strategies through simulations. While we apply our proposed model to data from a leading financial institution, our approach is equally applicable to other retail settings. The results show that customers’ choices of services and channels are sensitive to process time by type of channel. A 10% increase in process time through non-mobile channels leads to a nearly 14% increase in utilization of mobile banking channel. Therefore, retailing firms could potentially influence customers’ choice of different channels by changing channel-specific process times. Motivated by these findings, we present and compare performances across five different policies, in promoting the usage of mobile channel. Drawing on our simulation results, we also make personalized policy recommendations to firms facing different levels of financial constraints. For those with financial constraints, we recommend a policy of increasing process time for a selected subset of service requests through non-mobile channels. Firms not constrained by the resources might be better off improving process time with the mobile channel by targeting customers identified as having a better relationship with the firm. |
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