Presentation on theme: "Www.rockresearch.com Trends in e-Services, Beliefs about Service Technologies, and Issues Researching the Category: The National Technology Readiness Survey."— Presentation transcript:
Trends in e-Services, Beliefs about Service Technologies, and Issues Researching the Category: The National Technology Readiness Survey Charles L. Colby, President Gina Woodall, Vice President Rockbridge Associates, Inc. For info, contact: Charles Colby –
Discussion Points Today NTRS Research Program Overview of Consumer Techno- Readiness TR Segmentation (Typology Based on Latent Class Analysis) Trends in e-Services Issues in Research e-Services
Our Research Program National Technology Readiness Survey –Authored by Parasuraman and Rockbridge –Sponsored by the Center for Excellence in Service, R.H. Smith School of Business, University of Maryland –Replicated in 1999, 2000, 2001, 2002, 2004, 2005/6; 2007 in field now –Nationally representative telephone survey through 2004 –Hybrid Web/Phone Survey starting in 2005/6 Other efforts in dozens of countries
Technology Readiness Index (TRI), a Multi- Item Scale to Measure Readiness to Embrace New Technologies, A. Parasuraman, Journal of Service Research, Vol. 2, No. 4, (2000) Techno-Ready Marketing: How and Why Your Customers Adopt Technology (Parasuraman & Colby: Free Press, April 2001) Sources
8 years of Research What are we learning about the consumer behavior of technology adoption?
What is Technology Readiness? (TR) TR refers to peoples propensity to embrace and use new technologies for accomplishing goals in home life and at work TR reflects an overall state-of-mind; it is not a measure of competence It describes the person, not the technology
LO TR HI TR Technology not for ordinary people Distrust tech support Want the basic model Technology fails at worst time E-commerce not safe Need confirmation that technology works Prefer talking to a person Technology gives control Technology more convenient Want most advanced technology Computers expand hours of business Want to tailor technology Thought leader First to acquire new technology Keep up with developments Like high-tech gadgets Technology Readiness Distribution
Optimism: Positive view of technology; belief that it offers increased control, flexibility and efficiency Innovativeness: Tendency to be a technology pioneer and thought leader Discomfort: Perceived lack of control over technology and a feeling of being overwhelmed by it Insecurity: Distrust of technology and skepticism about it working properly TR Dimensions
The Technology Readiness Index (TRI): A Multi-Item Measure 36 agreement scaled attributes 4 sub-scales for measuring individual dimensions of TR Many studies use an abbreviated 10 item or 6 item index The scale is available to scholars without charge Note: scale is called TechQual® in a commercial setting
The TRI is Highly Stable over Time Techno-Readiness was highly stable from 1999 to 2004 TR does not change readily on an individual basis
Why did TR Increase in 2005/6? There is a high degree of stability over time – TR items appear to be firm beliefs rather than prevailing opinions that shift in response to market change –Over time, consumers have gained greater confidence in online services and the internet, which make up some of the items in the index –In 2005, it was necessary to switch to a combination web/phone methodology (discussed later), which had some impact
Conclusions The TRI continues to be a strong predictor and explanatory variable in tech adoption –Example: a recent study of 9 countries (U.S., Canada, China, India, Japan, Russia, Turkey, Brazil, Mexico) In the future, we need to focus on more tech neutral questions, of which there are many in the scale
A Technology Segmentation Using a Typology to Describe Technology Consumer Behavior
Advantages of a Segmentation View (or Typology) Recognizes that beliefs about technology do not follow a continuum –Example: Pioneers have a love/ hate relationship with technology A typology allows a differentiated marketing view: –Explorers: enlist help to identify innovations –Pioneers: provide hand-holding –Skeptics: convince them of benefits –Paranoids: reassure about safety –Laggards: sell them last generation technology
Segmentation Approach The typology used in Techno-Ready Marketing was based on K-Means, a robust and easy to use clustering method Researchers have since relied on methods with greater stability and theoretical underpinning, including Latent Class (LCA) and Q-Factoring We recently validated the segments using LCA on a data set including multiple years of NTRS data* –Result: a 64% overlap between K-Means and LCA segments –Qualitatively, a similar typology emerged *This was done in support of a TR-related research project by Ann Massey and Mitzi Montoya-Weiss, Indiana University.
LCA Segments (including deviation from means on 4 components) Segment (original name per k-means) %* TR In- dex** Drivers (Positive)Inhibitors (Negative) Opti- mism Innov- ativeness Dis- comfort In- security Skeptics 35% Paranoids 20% Explorers 18% Pioneers 17% Laggards 10% *Unweighted data. **100 = Average per 1999 baseline.
NTRS: 1999 – 2006 What are we learning about the e-Service marketplace?
NTRS shows consistent growth in Internet access at home, while exposure at work has not changed over 7 years 83% of consumers have access to the Internet somewhere (33% access it outside of work or home) NTRS also tracks home networks, broadband, and internet identity Connectivity Trends in the U.S.
E-Commerce is Growing Consumers are moving forward cautiously in buying online, so e-commerce is now commonplace
There is continued growth in online banking Online billpaying is another rapidly growing area Consumers are moving beyond their banks, going directly to billers sites e-Finance is a Booming Category
C2C Commerce The internet creates a growing market for consumers to deal directly, using online classifieds and auction sites
Expect a Revolution in e-Services
Factors Holding Back the e-Service Revolution in the U.S. Promises for the Future –Fully mobile commerce –Location-free entertainment –Voice/data convergence in service transactions –Personalized mini- brands –Web-conferenced interactions Issues in U.S. –Slow connectivity (behind Asia and Europe) –Slow introduction of 3G, 4G and Wimax –Limited consumer awareness of new technologies* –Lingering insecurity *In the 2005/6 NTRS, only 18% were at least a little familiar with 3G
Issues in Researching e-Services Changing Sampling Frames and their Impact
Why NTRS Changed Methodologies In 2005/6, the NTRS was fielded using ½ telephone sample and ½ web sample –Telephone: Random Digit Dialing (once the gold standard) –Web: utilized a web panel by Survey Sampling Incorporated
Issues with Telephone Sampling Researchers are not allowed to contact cell phones for interviewing There has been an increasing number of cell phone only households due to… –Households never signing up for wireline service (usually younger, more mobile) –Number portability legislation allowing migration of wireline numbers to cell phones –Estimated to be 10.3% in early 2006 Phone surveys also face problems with voice mail and caller ID being used to screen interviewing
Issues with Web Sampling There is no rigorous probability sampling method for /web surveys –Lack of an exhaustive sampling frame –Researcher code of conduct (CASRO) prohibits unsolicited survey invitations Researchers must rely on consumer panels, which have a range of potential problems –While possible to balance for demographics… –Other biases cannot be controlled Excludes the 1/6 of consumers who are not online –At this point, the % coverage of telephone and web frames is about the same
Issues with Combining Data Scale usage by Respondents – note that TR items are fully anchored to help with this issue Different technology beliefs and behaviors after controlling for demographics and access Complex weighting steps needed to address differences in frames
Future Steps for NTRS The 2007 NTRS is in the field now The focus will be on Greenovators (the intersection between Green awareness and technology) Possible areas to explore: –Should the TRI list be refined, e.g., culling less stable measures? –Exploring TRI on a global scale (we now have a 9 country study using 10 items)