equity: Which best predicts

Brand equity surveys or

social media-based brand

equity: Which best predicts

future firm performance?

Agenda

Data collection Methodology

Results Conclusion Limitiations Implications &

Introduction (1)

• Assessing and comparing ROI → optimal resource allocation1

• Determing value intangible assets → accurate prediction firm performance2 • Shift in value from tangible to intangible

assets3 17,1 32,1 68,0 80,0 84,0 83,1 68,0 32,0 20,0 _16,0 1975 1985 1995 2005 2018 R a ti o o f v a lu e o f a ss e ts ( in % )

Time (in years)

Value of tangible assets vs. intangible assets for S&P companies, 1975-2018

Introduction (2)

• Focus on measuring CBBE

• Survey current measure brand equity • Costly

• Time-consuming • Once in a while

• Historical perspective

RQ: Is SMBBE a better method in predicting future firm performance than

traditionally measured CBBE?

• Social media-based brand equity (SMBBE)

Literature review (1)

• Three approaches of brand equity4 • Customer-mind set

• Product-market outcomes • Financial-market outcomes • Aaker five constructs5

• Brand loyalty

• Brand awareness • Perceived quality • Brand associations

• Other brand assets (brand relevance)

• BAV four pillars • Knowledge • Relevance • Esteem

• Differentiation

Literature review (2)

• Social media

• Sharing information

• Interpersonal relationships • Social capital

• SMBBE measured by Twitter • Popularity

• Relevance

Data collection

Three data sources

BAV data

• Contains proxies SMBBE data

• Twitterscraper

Firm performance data

• Five performance metrics • Forward-and

backward-First quarter 2008 →

Second quarter 2010

Unique final dataset

20 firms

Methodology

• Collecting interactions

• Sentiment analyses

• Score dimension twofold

Results (1)

• Predictors correlation

• BAV dimensions

• Not Granger caused by SMBBE • Able to predict future BAV

• High cross-correlation → Little incremental value

• SMBBE dimensions

• Vary more over time

• Low cross-correlation → Much new information • Low cross-correlation → Volatile metric

Results (2)

• SMBBE relevance sentiment best-predicting

• Akaike weight 96.66%

• 3/5 metrics predictor future value

• SMBBE relevance ratio second-best

• Akaike weights >0.00%

• 3/5 metrics predictor future value

• Combining metrics performs even better

• Better results for 4/5 metrics

• BAV dimensions not good predictors

• Different timeframe • Different firms

Results (3)

• H1a-H1e rejected

• Lagged BAV dimension explains future BAV • BAV dimensions are stable/little variance • Granger causality harder to establish

• Moderate support H2

• 4/9 SMBBE dimensions predictor of future ROE • None BAV dimensions predictors

• Moderate support H3

• 7/15 parameters significant interaction effect

• H4 rejected

Conclusion

• SMBBE better predictor than traditional measure

• Single SMBBE dimensions > single BAV dimension

• Combining SMBBE dimensions > combining BAV dimensions

• 4/9 SMBBE dimensions sign. predictor future firm performance

• SMBBE better subsitute for traditional measured CBBE

Limitations

• Timeframe relatively short

• Data is old

• Not every firm Twitter account

• NCAR

• Modern firms

• Less users Twitter

• Less representative

• Large US firms

Implications & future reseach

• SMBBE dashboard

• enhances decision-making

• Enables optimal resource allocation

• Advice on dashboard

• Include multiple SMBBE dimensions • Combine with BAV dimensions

• Other social media networks • Internal data

• Feasibilty

• Same effects other sources

• Gives valuable insights

Reference list

• 1_{Schiuma, G., Lerro, A., Costa, R., & Evangelista, S. (2008). An AHP approach to assess brand intangible assets. Measuring Business} Excellence.

• 2_{Saaty, T. L., Vargas, L. G., & Dellmann, K. (2003). The allocation of intangible resources: the analytic hierarchy process and linear} programming. Socio-Economic Planning Sciences, 37(3), 169-184.

• 3_{Ocean, T. O. M. O. (2009). Ocean Tomo's Intangible Asset Market Value Study. Acedido em, 15.}

• 4_{Keller, K. L. (2003). Understanding brands, branding and brand equity. Interactive Marketing, 5(1), 7-20.} • 5_{Aaker, D. A., & Equity, M. B. (1991). The Free Press. New York, 206.}

• 6_{Aaker, D. A., & Jacobson, R. (2001). The value relevance of brand attitude in high-technology markets.}

• 7_{Aaker, D. A., & Jacobson, R. (1994). The financial information content of perceived quality. Journal of marketing research, 31(2),} 191-201.

• 8_{Mizik, N., & Jacobson, R. (2008). The financial value impact of perceptual brand attributes. Journal of Marketing Research, 45(1),} 15-32.

• 9_{Stahl, F., Heitmann, M., Lehmann, D. R., & Neslin, S. A. (2012). The impact of brand equity on customer acquisition, retention, and} profit margin. Journal of marketing, 76(4), 44-63.