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Meta-analysis: integrating accumulated knowledge

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Abstract

Building a foundation of marketing theory requires developing effective ways to aggregate research results. Meta-analyses that accumulate knowledge within a research domain is an important means for summarizing research findings and increasingly is being conducted in various substantive marketing domains. Moderator analysis and structural models using meta-analytic inputs have emerged as a powerful means to advance current knowledge in a research domain, and, importantly, identify fruitful areas for future inquiry. This article reviews the growth of meta-analysis in marketing and identifies several important issues researchers must consider when conducting and reporting a meta-analysis.

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References

  • Albers, S., Mantrala, M. K., & Sridhar, S. (2010). Personal selling elasticities: A meta-analysis. Journal of Marketing Research, 47(5), 840–853.

    Article  Google Scholar 

  • Assmus, G., Farley, J. U., & Lehmann, D. R. (1984). How advertising affects sales: Meta-analysis of econometric results. Journal of Marketing Research, 21, 65–74.

    Article  Google Scholar 

  • Beal, D. J., Corey, D. M., & Dunlap, W. P. (2002). On the bias of Huffcutt and Arthur's (1995) procedure for identifying outliers in the meta-analysis of correlations. Journal of Applied Psychology, 87(3), 583–589.

    Article  Google Scholar 

  • Borenstein, M., Higgins, J. P., Hedges, L. V., & Rothstein, H. R. (2009). Introduction to meta-analysis. Chichester: Wiley.

    Book  Google Scholar 

  • Borenstein, M., Higgins, J. P., Hedges, L. V., & Rothstein, H. R. (2010). A basic introduction to fixed-effect and random-effects models for meta-analysis. Research Synthesis Methods, 1, 97–111.

    Article  Google Scholar 

  • Borenstein, M., Higgins, J. P., Hedges, L. V., & Rothstein, H. R. (2017). Basics of meta-analysis: I2 is not an absolute measure of heterogeneity. Research Synthesis Methods, 8, 5–18.

    Article  Google Scholar 

  • Brown, S. P., & Peterson, R. A. (1993). Antecedents and consequences of salesperson job satisfaction: Meta-analysis and assessment of causal effects. Journal of Marketing Research, 30, 63–77.

    Article  Google Scholar 

  • Brown, S. P., & Stayman, D. M. (1992). Antecedents and consequences of attitude toward the ad: A meta-analysis. Journal of Consumer Research, 19, 34–51.

    Article  Google Scholar 

  • Brown, S. P., Homer, P. M., & Inman, J. J. (1998). A meta-analysis of relationships between ad-evoked feelings and advertising responses. Journal of Marketing Research, 35, 114–126.

    Article  Google Scholar 

  • Campbell, J. P., Daft, R. L., & Hulin, C. L. (1982). What to study: Generating and developing research questions. Beverly Hills: Sage Publications, Inc..

    Google Scholar 

  • Carlson, J. P., Vincent, L. H., Hardesty, D. M., & Bearden, W. O. (2008). Objective and subjective knowledge relationships: A quantitative analysis of consumer research findings. Journal of Consumer Research, 35, 864–876.

    Article  Google Scholar 

  • Chang, W., & Taylor, S. A. (2016). The effectiveness of customer participation in new product development: A meta-analysis. Journal of Marketing, 80, 47–64.

    Article  Google Scholar 

  • Cheung, M.W.-L. (2015). Meta-analysis: A structural equation modeling approach. Chichester: John Wiley & Sons

  • Churchill Jr, G. A., & Peter, J. P. (1984). Research design effects on the reliability of rating scales: A meta-analysis. Journal of Marketing Research, 21, 360–375.

    Article  Google Scholar 

  • Churchill Jr., G. A., Ford, N. M., Hartley, S. W., & Walker Jr., O. C. (1985). The determinants of salesperson performance: A meta-analysis. Journal of Marketing Research, 22, 103–118.

    Article  Google Scholar 

  • Cochran, W. G. (1950). The comparison of percentages in matched samples. Biometrika, 37(3/4), 256–266.

    Article  Google Scholar 

  • Compeau, L. D., & Grewal, D. (1998). Comparative price advertising: An integrative review. Journal of Public Policy & Marketing, 17(2), 257–273.

    Google Scholar 

  • Conchar, M. P., Crask, M. R., & Zinkhan, G. M. (2005). Market valuation models of the effect of advertising and promotional spending: A review and meta-analysis. Journal of the Academy of Marketing Science, 33(4), 445–460.

    Article  Google Scholar 

  • Cooper, H. M. (1982). Scientific guidelines for conducting integrative research reviews. Review of Educational Research, 52(Summer), 291–302.

    Article  Google Scholar 

  • Cox III, E. P., Wogalter, M. S., Stokes, S. L., & Tipton Murff, E. J. (1997). Do product warnings increase safe behavior? A meta-analysis. Journal of Public Policy & Marketing, 16(2), 195–204.

    Google Scholar 

  • Crosno, J. L., & Brown, J. R. (2015). A meta-analytic review of the effects of organizational control in marketing exchange relationships. Journal of the Academy of Marketing Science, 43(3), 297–314.

    Article  Google Scholar 

  • Crosno, J. L., & Dahlstrom, R. (2008). A meta-analytic review of opportunism in exchange relationships. Journal of the Academy of Marketing Science, 36(2), 191–201.

    Article  Google Scholar 

  • de Matos, C. A., & Vargas Rossi, C. A. (2008). Word-of-mouth communications in marketing: A meta-analytic review of the antecedents and moderators. Journal of the Academy of Marketing Science, 36(4), 578–596.

    Article  Google Scholar 

  • Duval, S. J., & Tweedie, R. L. (2000). Trim and fill: A simple funnel plot-based method of testing and adjusting for publication bias in meta-analysis. Biometrics, 56(2), 455–463.

    Article  Google Scholar 

  • Edeling, A., & Fischer, M. (2016). Marketing’s impact on firm value: Generalizations from a meta-analysis. Journal of Marketing Research, 53(4), 515–534.

    Article  Google Scholar 

  • Eisend, M. (2009). A meta-analysis of humor in advertising. Journal of the Academy of Marketing Science, 37(2), 191–203.

    Article  Google Scholar 

  • Eisend, M. (2010). A meta-analysis of gender roles in advertising. Journal of the Academy of Marketing Science, 38, 418–440.

    Article  Google Scholar 

  • Eisend, M. (2015). Have we progressed marketing knowledge? A meta-meta-analysis of effect sizes in marketing research. Journal of Marketing, 79(3), 23–40.

    Article  Google Scholar 

  • Eisend, M., & Küster, F. (2011). The effectiveness of publicity versus advertising: A meta-analytic investigation of its moderators. Journal of the Academy of Marketing Science, 39(6), 906–921.

    Article  Google Scholar 

  • Estelami, H., & Lehmann, D. R. (2001). The impact of research design on consumer price recall accuracy: An integrative review. Journal of the Academy of Marketing Science, 29(1), 36–49.

    Article  Google Scholar 

  • Estelami, H., Lehmann, D. R., & Holden, A. C. (2001). Macro-economic determinants of consumer price knowledge: A meta-analysis of four decades of research. International Journal of Research in Marketing, 18(4), 341–355.

    Article  Google Scholar 

  • Farley, J. U., Lehman, D. R., & Ryan, M. J. (1981). Generalizing from ‘imperfect’ replication. Journal of Business, 54, 597–610.

    Article  Google Scholar 

  • Farley, J. U., Lehmann, D. R., & Sawyer, A. (1995). Empirical generalizations using meta-analysis. Marketing Science, 13(3), G36–G46.

    Article  Google Scholar 

  • Fern, E. F., & Monroe, K. B. (1996). Effect-size estimates: Issues and problems in interpretation. Journal of Consumer Research, 23(2), 89–105.

    Article  Google Scholar 

  • Fern, E. F., Monroe, K. B., & Avila, R. A. (1986). Effectiveness of multiple request strategies: A synthesis of research results. Journal of Marketing Research, 23, 144–152.

    Article  Google Scholar 

  • Franke, G. R. (2001). Applications of meta-analysis for marketing and public policy: A review. Journal of Public Policy & Marketing, 20(2), 186–200.

    Article  Google Scholar 

  • Franke, G.R., & Park, J-E. (2006). Salesperson adaptive selling behavior and customer orientation: A meta-analysis. Journal of Marketing Research, 43 (November), 693–702.

  • Geyskens, I., Steenkamp, J.-B. E. M., & Kumar, N. (1999). A meta-analysis of satisfaction in marketing channel relationships. Journal of Marketing Research, 36, 223–238.

    Article  Google Scholar 

  • Geyskens, I., Krishnan, R., Steenkamp, J. B. E., & Cunha, P. V. (2009). A review and evaluation of meta-analysis practices in management research. Journal of Management, 35(2), 393–419.

    Article  Google Scholar 

  • Glass, G. V. (1976). Primary, secondary, and meta-analysis of research. Educational Researcher, 5(10), 3–8.

    Article  Google Scholar 

  • Glass, G. V., McGaw, B., & Smith, M. L. (1981). Meta-analysis in social research. Beverly Hills: Sage Publications.

    Google Scholar 

  • Greenwald, A. G. (1975). Consequences of prejudice against the null hypothesis. Psychological Bulletin, 82, 1–20.

    Article  Google Scholar 

  • Grewal, D., Kavanoor, S., Fern, E. F., Costley, C., & Barnes, J. (1997). Comparative versus noncomparative advertising: A meta-analysis. Journal of Marketing, 61, 1–15.

    Article  Google Scholar 

  • Grinstein, A. (2008). The effect of market orientation and its components on innovation consequences: A meta-analysis. Journal of the Academy of Marketing Science, 36, 166–173.

    Article  Google Scholar 

  • Heath, T. B., & Chatterjee, S. (1995). Asymmetric decoy effects on lower-quality versus higher-quality brands: Meta-analytic and experimental evidence. Journal of Consumer Research, 22, 268–284.

    Article  Google Scholar 

  • Hedges, L. V., & Olkin, I. (1985). Statistical methods for meta-analysis. New York: Academic Press.

    Google Scholar 

  • Henard, D. H., & Szymanski, D. M. (2001). Why some new products are more successful than others. Journal of Marketing Research, 38, 362–375.

    Article  Google Scholar 

  • Higgins, J., & Thompson, S. G. (2002). Quantifying heterogeneity in a meta-analysis. Statistics in Medicine, 21(11), 1539–1558.

    Article  Google Scholar 

  • Higgins, J., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003). Measuring inconsistency in meta-analyses. British Medical Journal, 327, 557–560.

    Article  Google Scholar 

  • Hogreve, J., Iseke, A., Derfuss, K., & Eller, T. (2017). The service–profit chain: A meta-analytic test of a comprehensive theoretical framework. Journal of Marketing, 81(3), 41–61.

    Article  Google Scholar 

  • Homburg, C., Klarmann, M., Reimann, M., & Schilke, O. (2012). What drives key informant accuracy? Journal of Marketing Research, 49(4), 594–608.

    Article  Google Scholar 

  • Huffcutt, A. I., & Arthur, W. (1995). Development of a new outlier statistic for meta-analytic data. Journal of Applied Psychology, 89(2), 327–334.

    Article  Google Scholar 

  • Hunter, J. E. (2001). The desperate need for replications. Journal of Consumer Research, 28, 149–158.

    Article  Google Scholar 

  • Hunter, J. E., & Schmidt, F. L. (1990). Methods of meta-analysis. Correcting error and bias in research findings. Thousand Oaks: Sage Publications, Inc..

    Google Scholar 

  • Hunter, J. E., & Schmidt, F. L. (2004). Methods of meta-analysis: Correcting error and bias in research findings (2nd ed.). Thousand Oaks: Sage Publications, Inc..

    Book  Google Scholar 

  • Hunter, J. E., Schmidt, F. L., & Jackson, G. B. (1982). Meta-analysis: Cumulating research findings across studies. Beverly Hills: Sage Publications, Inc..

    Google Scholar 

  • Jak, S. (2015). Meta-analytic structural equation modelling. Cham: Springer International Publishing.

  • Janiszewski, C., Noel, H., & Sawyer, A. G. (2003). A meta-analysis of the spacing effect in verbal learning: Implications for research on advertising repetition and consumer memory. Journal of Consumer Research, 30, 138–149.

    Article  Google Scholar 

  • Keller, P. A., & Lehmann, D. R. (2008). Designing effective health communications: A meta-analysis. Journal of Public Policy & Marketing, 27(2), 117–130.

    Article  Google Scholar 

  • Keller, P. A., Lehmann, D. R., & Milligan, K. J. (2009). Effectiveness of corporate well-being programs. Journal of Macromarketing, 29(3), 279–302.

    Article  Google Scholar 

  • Kirca, A. H., Jayachandran, S., & Bearden, W. O. (2005). Market orientation: A meta-analytic review and assessment of its antecedents and impact on performance. Journal of Marketing, 69, 24–41.

    Article  Google Scholar 

  • Knoll, J., & Matthes, J. (2017). The effectiveness of celebrity endorsements: A meta-analysis. Journal of the Academy of Marketing Science, 45(1), 55–75.

    Article  Google Scholar 

  • Krasnikov, A., & Jayachandran, S. (2008). The relative impact of marketing, research-and-development, and operations capabilities on firm performance. Journal of Marketing, 72, 1–11.

    Article  Google Scholar 

  • Krishna, A., Briesch, R., Lehmann, D. R., & Yuan, H. (2002). A meta-analysis of the impact of price presentation on perceived savings. Journal of Retailing, 78, 101–118.

    Article  Google Scholar 

  • Lipsey, M. W., & Wilson, D. B. (2001). Practical meta-analysis (p. 49). Thousand Oaks: Sage Publications.

    Google Scholar 

  • Monroe, K.B., & Krishnan, R. (1983). A procedure for integrating outcomes across studies. Advances in Consumer Research, 10, R. P. Bagozzi and A. M. Tybout (eds.), 503–508.

  • Motyka, S., Grewal, D., Puccinelli, N. M., Roggeveen, A. L., Avnet, T., Daryanto, A., & Wetzels, M. (2014). Regulatory fit: A meta-analytic synthesis. Journal of Consumer Psychology, 24(3), 394–410.

    Article  Google Scholar 

  • Notani, A. S. (1998). Moderators of perceived behavioral control's predictiveness in the theory of planned behavior: A meta-analysis. Journal of Consumer Psychology, 7(3), 247–272.

    Article  Google Scholar 

  • Orsingher, C., Valentini, S., & de Angelis, M. (2010). A meta-analysis of satisfaction with complaint handling in services. Journal of the Academy of Marketing Science, 38(2), 169–186.

    Article  Google Scholar 

  • Orwin, R. G. (1983). A fail-safe N for effect size in meta-analysis. Journal of Educational Statistics, 8(2), 157–159.

    Article  Google Scholar 

  • Palmatier, R. W., Dant, R. P., Grewal, D., & Evans, K. R. (2006). Factors influencing the effectiveness of relationship marketing: A meta-analysis. Journal of Marketing, 70, 136–153.

    Article  Google Scholar 

  • Palmatier, R. W., Houston, M. B., & Hulland, J. (2017). Review articles: Purpose, process, and structure. Journal of the Academy of Marketing Science, 46(1). https://doi.org/10.1007/s11747-017-0563-4.

  • Peter, J. P., & Churchill Jr., G. A. (1986). Relationships among research design choices and psychometric properties of rating scales: A meta-analysis. Journal of Marketing Research, 23, 1–10.

    Article  Google Scholar 

  • Peterson, R. A. (1994). A meta-analysis of Cronbach's coefficient alpha. Journal of Consumer Research, 21(2), 381–391.

    Article  Google Scholar 

  • Peterson, R. A. (2001). On the use of college students in social science research: Insights from a second-order meta-analysis. Journal of Consumer Research, 28(3), 450–461.

    Article  Google Scholar 

  • Peterson, R. A., & Brown, S. P. (2005). On the use of beta coefficients in meta-analysis. Journal of Applied Psychology, 90(1), 175–181.

    Article  Google Scholar 

  • Peterson, R. A., Albaum, G., & Beltramini, R. F. (1985). A meta-analysis of effects sizes in consumer behavior experiments. Journal of Consumer Research, 12, 97–103.

    Article  Google Scholar 

  • Pick, D., & Eisend, M. (2014). Buyers’ perceived switching costs and switching: A meta-analytic assessment of their antecedents. Journal of the Academy of Marketing Science, 42(2), 186–204.

    Article  Google Scholar 

  • Pillemer, D. B., & Light, R. (1980). Synthesizing outcomes: How to use research evidence from many studies. Harvard Educational Review, 50, 176–195.

    Article  Google Scholar 

  • Puccinelli, N.M., et al. (2013). Are men seduced by red? The effect of red versus black prices on price perceptions. Journal of Retailing, 89.2, 115–125.

  • Rao, A. R., & Monroe, K. B. (1989). The effect of price, brand name, and store name on buyers' perceptions of product quality: An integrative review. Journal of Marketing Research, 26, 351–357.

    Article  Google Scholar 

  • Rosario, A. B., Sotgiu, F., De Valck, K., & Bijmolt, T. H. (2016). The effect of electronic word of mouth on sales: A meta-analytic review of platform, product, and metric factors. Journal of Marketing Research, 53, 297–318.

    Article  Google Scholar 

  • Rosenthal, R. (1979). The "file drawer problem" and tolerance for null results. Psychological Bulletin, 86(3), 638–641.

    Article  Google Scholar 

  • Rosenthal, R. (1980). Summarizing significance levels. In R. Rosenthal (Ed.), New Directions for Methodology of Social and Behavioral Science: Quantitative Assessment of Research Domains, (5) (pp. 33–46). San Francisco: Jossey-Bass.

    Google Scholar 

  • Rosenthal, R. (1982). Valid interpretation of quantitative research results. In D. Brinberg & L. Kidder (Eds.), New Directions for Methodology of Social and Behavioral Science: Forms of Validity in Research, (12) (pp. 59–75). San Francisco: Jossey-Bass.

    Google Scholar 

  • Rosenthal, R. (1984). Meta-analytic procedures for social research. Beverly Hills: Sage Publications.

    Google Scholar 

  • Rosenthal, R., & DiMatteo, M. R. (2001). Meta-analysis: Recent developments in quantitative methods for literature reviews. Annual Review of Psychology, 52(1), 59–82.

    Article  Google Scholar 

  • Rosenthal, R., & Rosnow, R. L. (2008). Essentials of behavioral research: Methods and data analysis (3rd ed.). Boston: McGraw-Hill.

    Google Scholar 

  • Rosenthal, R., & Rubin, D. B. (1979). A note on percent variance explained as a measure of the importance of effects. Journal of Applied Social Psychology, 9(5), 395–396.

    Article  Google Scholar 

  • Rosenthal, R., & Rubin, D. B. (1982). A simple, general purpose display of magnitude of experimental effect. Journal of Educational Psychology, 74(2), 166.

    Article  Google Scholar 

  • Rubera, G., & Kirca, A. H. (2012). Firm innovativeness and its performance outcomes: A meta-analytic review and theoretical integration. Journal of Marketing, 76, 130–147.

    Article  Google Scholar 

  • Scheer, L. K., Miao, C. F., & Palmatier, R. W. (2015). Dependence and interdependence in marketing relationships: Meta-analytic insights. Journal of the Academy of Marketing Science, 43(6), 694–712.

    Article  Google Scholar 

  • Scheibehenne, B., Greifeneder, R., & Todd, P. M. (2010). Can there be too many options? A meta-analytic review of choice overload. Journal of Consumer Research, 37(3), 409–425.

    Article  Google Scholar 

  • Sethuraman, R., Tellis, G. J., & Briesch, R. A. (2011). How well does advertising work? Generalizations from meta-analysis of brand advertising elasticities. Journal of Marketing Research, 48(3), 457–471.

    Article  Google Scholar 

  • Sheppard, B.H., Hartwick, J., & and Warshaw, P.R. (1988). The theory of reasoned action: A meta-analysis of past research with recommendations for modifications and future research. Journal of Consumer Research, 15, 325–343.

  • Spangenberg, E. R., & Greenwald, A. G. (1999). Social influence by requesting self-prophecy. Journal of Consumer Psychology, 8(1), 61–89.

    Article  Google Scholar 

  • Steenkamp, J.-B. E. M., & Geyskens, I. (2012). Transaction cost economics and the roles of national culture: A test of hypotheses based on Inglehart and Hofstede. Journal of the Academy of Marketing Science, 40, 252–270.

    Article  Google Scholar 

  • Sultan, F., Farley, J. U., & Lehmann, D. R. (1990). A meta-analysis of applications of diffusion models. Journal of Marketing Research, 27, 70–77.

    Article  Google Scholar 

  • Szymanski, D. M., & Busch, P. S. (1987). Identifying the generics-prone consumer: A meta-analysis. Journal of Marketing Research, 24, 425–431.

    Article  Google Scholar 

  • Szymanski, D. M., & Henard, D. H. (2001). Customer satisfaction: A meta-analysis of the empirical evidence. Journal of the Academy of Marketing Science, 29(1), 16–35.

    Article  Google Scholar 

  • Szymanski, D. M., Kroff, M. W., & Troy, L. C. (2007). Innovativeness and new product success: Insights from the cumulative evidence. Journal of the Academy of Marketing Science, 35, 35–52.

    Article  Google Scholar 

  • Tellis, G. J. (1988). The price elasticity of selective demand: A meta-analysis of econometric models of sales. Journal of Marketing Research, 25, 331–341.

    Article  Google Scholar 

  • Tellis, G. J., & Wernerfelt, B. (1987). Competitive price and quality under asymmetric information. Marketing Science, 6(3), 240–253.

    Article  Google Scholar 

  • Troy, L. C., Hirunyawipada, T., & Paswan, A. K. (2008). Cross-functional integration and new product success: An empirical investigation of the findings. Journal of Marketing, 72, 132–146.

    Article  Google Scholar 

  • Vadillo, M. A., Gold, N., & Osman, M. (2016). The bitter truth about sugar and willpower: The limited evidential value of the glucose model of ego depletion. Psychological Science, 27(9), 1207–1214.

    Article  Google Scholar 

  • Van den Bulte, C., & Stremersch, S. (2004). Social contagion and income heterogeneity in new product diffusion: A meta-analytic test. Marketing Science, 23(4), 530–554.

    Article  Google Scholar 

  • Van Laer, T., De Ruyter, K., Visconti, L. M., & Wetzels, M. (2014). The extended transportation-imagery model: A meta-analysis of the antecedents and consequences of consumers' narrative transportation. Journal of Consumer Research, 40(5), 797–817.

    Article  Google Scholar 

  • Verbeke, W., Dietz, B., & Verwaal, E. (2011). Drivers of sales performance: A contemporary meta-analysis. Have salespeople become knowledge brokers? Journal of the Academy of Marketing Science, 39(3), 407–428.

    Article  Google Scholar 

  • Viswesvaran, C., & Ones, D. S. (1995). Theory testing: Combining psychometric meta-analysis and structural equations modeling. Personnel Psychology, 48(4), 865–885.

    Article  Google Scholar 

  • Völckner, F., & Hoffmann, J. (2007). The price-perceived quality relationship: A meta-analytic review and assessment of its determinants. Marketing Letters, 18(3), 181–196.

    Article  Google Scholar 

  • Watson, G. F., Beck, J. T., Henderson, C. M., & Palmatier, R. W. (2015). Building, measuring, and profiting from customer loyalty. Journal of the Academy of Marketing Science, 43(6), 790–825.

    Article  Google Scholar 

  • Wells, W. D. (2001). The perils of N = 1. Journal of Consumer Research, 28, 494–498.

    Article  Google Scholar 

  • Wilson, E. J., & Sherrell, D. L. (1993). Source effects in communication and persuasion research: A meta-analysis of effect size. Journal of the Academy of Marketing Science, 21(2), 101–112.

    Article  Google Scholar 

  • Wright, M., & MacRae, M. (2007). Bias and variability in purchase intention scales. Journal of the Academy of Marketing Science, 35, 617–624.

    Article  Google Scholar 

  • You, Y., Vadakkepatt, G. G., & Joshi, A. M. (2015). A meta-analysis of electronic word-of-mouth elasticity. Journal of Marketing, 79(2), 19–39.

    Article  Google Scholar 

  • Yu, J., & Cooper, H. (1983). A quantitative review of research design effects on response rates to questionnaires. Journal of Marketing Research, 20, 36–44.

    Article  Google Scholar 

  • Zablah, A. R., Franke, G. R., Brown, T. J., & Bartholomew, D. E. (2012). How and when does customer orientation influence frontline employee job outcomes? A meta-analytic evaluation. Journal of Marketing, 76, 21–40.

    Article  Google Scholar 

  • Zlatevska, N., Dubelaar, C., & Holden, S. S. (2014). Sizing up the effect of portion size on consumption: A meta-analytic review. Journal of Marketing, 78, 140–154.

    Article  Google Scholar 

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Correspondence to Dhruv Grewal.

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The authors appreciate the feedback and insights shared by Michael Borenstein. They also appreciate the helpful comments of Gopalkrishnan Iyer. The authors also appreciate the feedback provided by the editor, AE and the reviewers.

Mark Houston served as Area Editor for this article.

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Table 5 Review of meta-analyses

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Grewal, D., Puccinelli, N. & Monroe, K.B. Meta-analysis: integrating accumulated knowledge. J. of the Acad. Mark. Sci. 46, 9–30 (2018). https://doi.org/10.1007/s11747-017-0570-5

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