36.7 Quality
Fundamental concept in many disciplines: policy, economics, consumer behavior, marketing strategy
Quality: attribute on which all (most) consumers prefer more to less (e.g., speed, reliability, durability, power). (Tellis and Wernerfelt 1987)
Market for quality (Klein and Leffler 1981): why quality commands a premium
Measurement of objective quality
Consumer reports (historically, until 2010)
Since 1935
Blind experiments with products
evaluated by experts
Problem: quality is multi-dimensional, composite quality depends on choice of dimensions and weights to combine them.
Solutions:
(Kopalle and Hoffman 1992): ranking products on quality not too noisy even if the weights are uncorrelated. but you still need attributes of quality to be positively correlated.
(Tellis and Johnson 2007): expert reviews: published quality ratings are good indicator of quality
(Tirunillai and Tellis 2014): wisdom of the crowds
36.7.1 (Tellis, Yin, and Niraj 2009) Network effects and quality in high tech
Evidence for market efficiency (defined as the best quality brand should have the largest market share)
Both quality and network effect affect market share flows (network effect > quality)
Network effect: “the increase in a consumer’s utility from a product when the number of other users of that product increases.” (p. 135)
Quality is defined as “a composite of a brand’s attributes, on each of which all consumers prefer more to less.” (p. 136) (e.g., reliability, performance, convenience).
Quality seems to be the driving force of the market (market share, return on investment, premium prices charged, advertising, perception of quality, stock market return, p. 136)
Theoretical cases: table 1
Sampling: Personal computer
Data: from International Data Corporation and Dataquest
36.7.2 (Peter N. Golder, Mitra, and Moorman 2012) An Integrative Framework for Quality
Quality processes:
Quality production process: focus on firms.. depedns on attribute design, process design, resoruce inptus and methods of controlling the production process.
Quality experience process: focus on customers
What the firm deliver and what the customer perceive can be different (relative to expectation) depends on
customer measurement knowledge
motivation
emotions
Experienced Attribute Quality vs. Delivered Attribute
Quality evaluation process: based on transactional and global judgments
“is the conversion of perceived attributes into an aggregated evaluation of quality, which is a summary jdugment of the customer’s experience of the firm’s offering.” (p. 9)
Evaluated aggregated quality is based on customer expertise and attribute characteristics
Customer Expectations: (1) “Will” expectation (2) “Ideal” expectation (3) “Should” expectation (perceived quality and fairness)
Quality is defined as ” a set of three distinct states of an offering’s attributes’ relative performance generated while producing, experiencing, and evaluating the offering.” (p. 2)
Figure 1 shows the framework
Typology of attribute types:
- Customer preference: homogeneous vs. heterogneous
- Measures ambiguity: unambiguous vs. ambiguous
| Customer preference | |||
|---|---|---|---|
| Homogenous | Heterogeneous | ||
| Measure ambiguity | Unambiguous | Universal attributes (flight delay) | Preference attributes (meal cuisine type, cabin temperature) |
| Ambiguous | Idiosyncratic attributes (art, beauty) |
36.7.3 (Tirunillai and Tellis 2014) Mining Quality from Consumer Reviews
use unsupervised LDA to measure quality dimensions in UGC
Data: 350,000 consumer reviews from (Tirunillai and Tellis 2012)
Results
- Dynamic analysis allows marketers to track the value of variables over time and dynamically map competitive brand positions on those dimensions.
| Market | Dimension | Across markets | Heterogeneity | Stability |
|---|---|---|---|---|
| Vertically differentiated (computer) | Objective dimensions dominate | Similiar | Low across dimensions | high over time |
| Horizontally differentiated (Shoes, toys) | Subjective dimensions dominate | Vary | High across dimensions | Low over time |