Skip to main content
SpringerLink
Log in

Selling, general, and administrative expense (SGA)-based metrics in marketing: conceptual and measurement challenges

  • Original Empirical Research
  • Published:
Journal of the Academy of Marketing Science Aims and scope Submit manuscript

A Correction to this article was published on 27 June 2018

This article has been updated

Abstract

Many studies use variables from the Compustat database to measure various marketing constructs, yet no clear guidelines detail which metrics correspond with which constructs. Justifications rest mainly on the ready availability of easy-to-use measures that seem related to a particular construct. As a result, various metrics have been utilized to capture the same construct, and the same metric—such as selling, general, and administrative expenses (SGA)—has been applied to capture vastly different constructs. But using SGA inappropriately can lead to biased estimates, questionable support for the hypotheses, and potentially misleading implications for research and practice. To test the validity of SGA for multiple relevant marketing and sales constructs, this study gathers data on benchmark variables from alternative data sources and applies a multitrait-multimethod (MTMM) approach. Results show that, in general, SGA has been applied too liberally in marketing contexts; SGA is an appropriate operationalization only for some constructs. This article provides guidelines for the proper conceptualization and operationalization of marketing constructs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

Change history

  • 27 June 2018

    The original version of this article unfortunately contained mistakes in Table 10. Data entries were incorrectly aligned under “Benchmark variables” and “Empirical test for SGA or modifications” columns. Please see below correct Table 10.

Notes

  1. Sometimes, use of SGA has been justified by intuitive reasoning. For example, because SGA budgets may be interpreted as a sign of financial resources of a firm, SGA appears to be a good proxy of marketing resources. Such operationalization suffers from lack of proper validation and can be hit or miss. Intuitively, there may be equally good or better proxies available within Compustat. For example, marketing resources which imply items such as cash, customer loyalty, brand equity, and patents could be measured using more direct and conceptually relevant measures such as “goodwill” or “total intangible assets.” One could even employ “working capital” or “cash and short-term investments” or “cash,” which are conceptually aligned to, and better capture, the resources a firm has available to cover its expenses. Of course, to choose the right operationalization one needs to establish content and construct validity, which we propose later.

  2. We also considered other data sources (e.g., Ebiquity, PIMS, Hoover) of benchmark variables but found them unsuitable. For example, Ebiquity reports data at the country level only, and its consultants advised us against aggregating these country-level data to obtain worldwide data. PIMS provides information at the strategic business unit level for participating companies, so it likewise is unsuitable. Hoover does not include any information related to marketing spending but rather provides qualitative information about big players only.

  3. We empirically validated the benchmark measures from these alternative sources by collecting data from annual reports of public and private companies. We thank an anonymous reviewer for this suggestion. We note here that these benchmark measures provide purer information on the three focal variables only: advertising expense, promotional expense, and salesforce expense. Whether these measures are also better than SGA at capturing any particular marketing construct depends on both content and construct validity.

  4. Outliers can have significant influences on correlation coefficients, so extreme outliers should be removed (Schwertman et al. 2004). We used Tukey’s (1977) formula: lower fence: Quartile 1–3*(Quartile 3 – Quartile 1); upper fence: Quartile 3 + 3*(Quartile 3 – Quartile 1). All values outside the fences were removed, which reduced the number of observations to 499. As we explain with our robustness checks, including these extreme outliers still provided similar results.

  5. There could be a potential sample selection bias as certain firms/industries may be overly represented in Advertising Age than in Compustat. We conducted propensity score matching to check if the smaller sample size used in the empirical analysis is representative of the broader sample drawn from Compustat. The results present no evidence of sample selection bias. The details of the matching procedure are available in Web Appendix 4. We thank an anonymous reviewer for this suggestion.

  6. Marketing spending, as used in the study for validation of SGA as a measure, has two subconstructs: advertising spending and promotional spending. Arguably, marketing spending on some activities such as advertising may bestow relatively longer-term benefits compared with spending on other activities such as promotions. However, considered in a comparative perspective, the spending construct is relatively short-term when compared with, say, the assets construct. Also, marketing literature that has used SGA—a short-term accounting variable—to measure spending has implicitly considered it short-term.

  7. We note the difference between marketing and sales functions, which are often organized and executed in different organizational departments and treated differently. Marketing involves activities to start and maintain a customer relationship (van Triest et al. 2009), such as advertising and promotional efforts, which generate customer awareness and establish brand preference. Sales seeks to stimulate actual purchases through sales force activities such as negotiations over price and delivery (Kotler and Rackham 2006).

  8. In addition to the two common modifications of SGA (SGA – ADV, SGA – R&D), we test another modification (SGA – ADV – R&D) to check if SGA has any significant marketing-related component, beyond ADV and R&D, which may justify its use as a measure of marketing constructs. Thus, scenario 1 includes four MTMM matrices: advertising spending measured using ADV whereas promotional spending measured using SGA, SGA – ADV, SGA – R&D, or SGA – ADV – R&D, respectively. Scenario 2 also uses four matrices, with promotional spending measured as ADV whereas advertising spending measured using each of the four SGA-based metrics.

  9. For the three MTMM matrices in scenario 1, perceptual assets are measured using ADV in each case, whereas intellectual assets are measured using SGA, SGA – ADV, or SGA – R&D. Scenario 2 also includes three matrices in which intellectual assets are always measured using ADV whereas perceptual assets use the three SGA-based metrics.

References

  • Achrol, R. S. (2012). Slotting allowances: A time series analysis of aggregate effects over three decades. Journal of the Academy of Marketing Science, 40(5), 673–694.

    Google Scholar 

  • Achrol, R. S., & Seo, J. H. (2011). In marketing channel theory and slotting allowances: An empirical analysis using quantile regression. American Marketing Association, 286–295.

  • Advertising Age (2016a). About global marketers 2015. Retrieved August 18, 2016, from http://adage.com/datacenter/globalmarketers2015/

  • Advertising Age (2016b). Methodology for 200 leading national advertisers, 2016 ed. Retrieved July 6, 2016, from http://adage.com/article/datacenter/methodology-200-leading-national-advertisers-2016-ed/304581/

  • Ailawadi, K. L., Borin, N., & Farris, P. W. (1995). Market power and performance: A cross-industry analysis of manufacturers and retailers. Journal of Retailing, 71(3), 211–248.

    Google Scholar 

  • Ambler, T., Kokkinaki, F., Puntoni, S., & Riley, D. (2001). Assessing market performance: The current state of metrics. Working paper, London Business School, Centre of Marketing.

  • Bagozzi, R. P. (1994). Measurement in marketing research: Basic principles of questionnaire design. In R. P. Bagozzi (Ed.), Principles of marketing research (pp. 1–49). Cambridge: Blackwell.

    Google Scholar 

  • Bahadir, S. C., Bharadwaj, S. G., & Srivastava, R. K. (2008). Financial value of brands in mergers and acquisitions: Is value in the eye of the beholder? Journal of Marketing, 72(6), 49–64.

    Google Scholar 

  • Balsam, S., Fernando, G. D., & Tripathy, A. (2011). The impact of firm strategy on performance measures used in executive compensation. Journal of Business Research, 64, 187–193.

    Google Scholar 

  • Banker, R. D., Mashruwala, R., & Tripathy, A. (2014). Does a differentiation strategy lead to more sustainable financial performance than a cost leadership strategy? Management Decision, 52(5), 872–896.

    Google Scholar 

  • Barney, J. B. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17, 99–120.

    Google Scholar 

  • Barney, J. B., & Arikan, A. (2001). The resource-based view: Origins and implications. In M. Hitt, R. Freeman, & J. Harrison (Eds.), Handbook of strategic management (pp. 124–185). Oxford: Blackwell.

    Google Scholar 

  • Bayus, B. L., Erickson, G., & Jacobson, R. (2003). The financial rewards of new product introductions in the personal computer industry. Management Science, 49(2), 197–210.

    Google Scholar 

  • Bell, D. E., & Gordon, D. S. (1999). The king-size company. Journal of Interactive Marketing, 13(1), 66–86.

    Google Scholar 

  • Bentley, K. A., Omer, T. C., & Sharp, N. Y. (2013). Business strategy, financial reporting irregularities, and audit effort. Contemporary Accounting Research, 30(2), 780–817.

    Google Scholar 

  • Berman, S. L., Wicks, A. C., Kotha, S., & Jones, T. M. (1999). Does stakeholder orientation matter? The relationship between stakeholder management models and firm financial performance. Academy of Management Journal, 42(5), 488–506.

    Google Scholar 

  • Bharadwaj, A. (2000). A resource-based perspective on information technology capability and firm. MIS Quarterly, 24(1), 169–196.

    Google Scholar 

  • Bharadwaj, S. G., Tuli, K. R., & Bonfrer, A. (2011). The impact of brand quality on shareholder wealth. Journal of Marketing, 75(5), 88–104.

    Google Scholar 

  • Borah, A., & Tellis, G. J. (2014). Make, buy, or ally? Choice of and payoff from announcements of alternate strategies for innovations. Marketing Science, 33(1), 114–133.

    Google Scholar 

  • Boulding, W., & Christen, M. (2008). Disentangling pioneering cost advantages and disadvantages. Marketing Science, 27(4), 699–716.

    Google Scholar 

  • Boyd, D. E., & Brown, B. P. (2012). Marketing control rights and their distribution within technology licensing agreements: A real options perspective. Journal of the Academy of Marketing Science, 40(5), 659–672.

    Google Scholar 

  • Bragg, S. M. (2010). Cost reduction analysis: Tools and strategies. New York: Wiley.

    Google Scholar 

  • Brink, D. V. D., Odekerken-Schröder, G., & Pauwels, P. (2006). The effect of strategic and tactical cause-related marketing on consumers’ brand loyalty. Journal of Consumer Marketing, 23, 15–25.

    Google Scholar 

  • Bruton, G. D., Keels, J. K., & Scifres, E. L. (2002). Corporate restructuring and performance: An agency perspective on the complete buyout cycle. Journal of Business Research, 55(9), 709–724.

    Google Scholar 

  • Campbell, D. T., & Fiske, D. W. (1959). Convergent and discriminant validation by the multitrait-multimethod matrix. Psychological Bulletin, 56, 81–105.

    Google Scholar 

  • Carton, R. B., & Hofer, C. W. (2006). In R. B. Carton & C. W. Hofer (Eds.), Measuring organizational performance. Cheltenham: Edward Elgar.

    Google Scholar 

  • Casadesus-Masanell, R., & Ricart, J. E. (2010). From strategy to business models and onto tactics. Long Range Planning, 43, 195–215.

    Google Scholar 

  • Cheng, M.-Y., Lin, J.-Y., Hsiao, T.-Y., & Lin, T. W. (2008). Censoring model for evaluating intellectual capital value drivers. Journal of Intellectual Capital, 9(4), 639–655.

    Google Scholar 

  • Churchill, G. A., Jr. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16, 64–73.

    Google Scholar 

  • Collins, C. J., & Han, J. (2004). Exploring applicant pool quantity and quality: The effects of early recruitment practice strategies, corporate advertising, and firm reputation. Personnel Psychology, 57, 685–717.

    Google Scholar 

  • Cook, V. J., Moult, W., & Spaeth, J. (2007). Marketing meets finance, working paper, 1–48.

  • Corona, R. (2009). Is Costco better than Walmart? A comparative analysis based on enterprise marketing efficiency. Working Paper, 1–34.

  • Corona, R. (2014). A comparative analysis of major US retailers based on enterprise marketing efficiency. Global Journal of Business Research, 8(4), 25–40.

    Google Scholar 

  • Darroch, J., & Miles, M. P. (2011). A research note on market creation in the pharmaceutical industry. Journal of Business Research, 64(7), 723–727.

    Google Scholar 

  • Dattero, R., White, E. M., & Janson, M. A. (1991). Methods for the identification of data outliers in interactive SQL. Journal of Database Administration, 2, 7–18.

    Google Scholar 

  • Day, G. S. (1994). The capabilities of market-driven organizations. Journal of Marketing, 58, 37–52.

    Google Scholar 

  • Demerjian, P., Lev, B., & McVay, S. (2012). Quantifying managerial ability: A new measure and validity tests. Management Science, 58(7), 1229–1248.

    Google Scholar 

  • DeVellis, R. F. (2012). Scale development. Thousand Oaks: Sage Publications.

    Google Scholar 

  • Ding, Y., Stolowy, H., & Tenenhaus, M. (2007). R&D productivity: an exploratory international study. Review of Accounting and Finance, 6(1), 86–101.

    Google Scholar 

  • Dinner, I. M. (2011). The interpretation of marketing actions and communications by the financial markets. Dissertation Thesis, 1–152.

  • Dinner, I. M., Mizik, N., & Lehmann, D. (2009). The unappreciated value of marketing: the moderating role of changes in marketing and R&D spending on valuation of earnings reports. Marketing Science Institute Special Report.

  • Dutta, S., Narasimhan, O., & Rajiv, S. (1999). Success in high-technology markets: Is marketing capability critical? Marketing Science, 18, 547–568.

    Google Scholar 

  • Dutta, S., Narasimhan, O., & Rajiv, S. (2005). Conceptualizing and measuring capabilities: Methodology and empirical application. Strategic Management Journal, 26, 277–285.

    Google Scholar 

  • Efendi, J., Kinney, M. R., Smith, K. T., & Smith, L. M. (2013). Marketing supply chain using B2B buy-side e-commerce systems: does adoption impact financial performance. Working Paper, 1–32.

  • Emory, W., & Cooper, D. R. (1991). Business research methods. Homewood: Irwin.

    Google Scholar 

  • Enache, L., & Srivastava, A. (2018). Should intangible investments be reported separately or commingled with operating expenses? Management Science: New evidence In press.

    Google Scholar 

  • Foster, G., & Gupta, M. (1994). Marketing, cost management, and management accounting. Journal of Management Accounting Research, 6, 63–77.

    Google Scholar 

  • Gaspar, J.-M., & Massa, M. (2006). Idiosyncratic volatility and product market competition. The Journal of Business, 79(6), 3125–3152.

    Google Scholar 

  • Gentry, R. J., & Shen, W. (2010). The relationship between accounting and market measures of firm financial performance: How strong is it? Journal of Managerial Issues, 22, 514–530.

    Google Scholar 

  • Grubaugh, S. G. (1987). Determinants of direct foreign investment. The Review of Economics and Statistics, 69(1), 149–152.

    Google Scholar 

  • Habib, A. (2017). Business strategy, overvalued equities, and stock price crash risk. Research in International Business and Finance, 39, 389–405.

    Google Scholar 

  • Haleblian, J., & Finkelstein, S. (1993). Top management team size, CEO dominance, and firm performance: The moderating roles of environmental turbulence and discretion. Academy of Management Journal, 36(4), 844–863.

    Google Scholar 

  • Hansen, D. R. (1990). Management accounting. Boston: PWS-KENT Publishing Company.

    Google Scholar 

  • Heeler, R. M., & Ray, M. L. (1972). Measure validation in marketing. Journal of Marketing Research, 9, 361–370.

    Google Scholar 

  • Higgins, D., Omer, T. C., & Phillips, J. D. (2015). The influence of a firm’s business strategy on its tax aggressiveness. Contemporary Accounting Research, 32(2), 674–702.

    Google Scholar 

  • Ho, L.-C. J., Liu, C.-S., & Ouyang, B. (2012). Bloated balance sheet, earnings management, and forecast guidance. Review of Accounting and Finance, 11(2), 120–140.

    Google Scholar 

  • Hornig, T., & Fischer, M. (2013). Validating financial brand equity metrics: How useful are brand valuation methods? Dissertation Thesis, 103–156.

  • Huang, R., Seow, G. S., & Shangguan, J. Z. (2011). Intangible investments and the pricing of corporate SGA expenses. The Journal of Business and Economic Studies, 17(2), 67–77.

    Google Scholar 

  • Im, K. S., Grover, V., & Teng, J. T. C. (2013). Do large firms become smaller by using information technology? Information Systems Research, 24(2), 470–491.

    Google Scholar 

  • Irvine, P. J., Park, S. S., & Yildizhan, C. (2016). Customer-base concentration, profitability, and the relationship life cycle. American Accounting Association, 91(3), 883–906.

    Google Scholar 

  • Kalaignanam, K., Kushwaha, T., Steenkamp, J.-B. E. M., & Tuli, K. R. (2013). The effect of CRM outsourcing on shareholder value: A contingency perspective. Management Science, 59(3), 748–769.

    Google Scholar 

  • Kalwani, M. U., & Narayandas, N. (1995). Relationships: Do they pay off for supplier firms? Journal of Marketing, 59(1), 1–16.

    Google Scholar 

  • Katsikeas, C. S., Morgan, N. A., Leonidou, L. C., & Hult, G. T. M. (2016). Assessing performance outcomes in marketing. Journal of Marketing, 80, 1–20.

    Google Scholar 

  • Kerlinger, F. (1986). Foundations of behavioral research. Fort Worth: Harcourt Brace Jovanovich.

    Google Scholar 

  • Kim, M., & McAlister, L. M. (2011). Stock market reaction to unexpected growth in marketing expenditure: Negative for sales force, contingent on spending level for advertising. Journal of Marketing, 75(7), 68–85.

    Google Scholar 

  • Koku, P. S. (2011). On the connection between R&D, selling expenditures, and profitability in the pharmaceutical industry revisited. Journal of Strategic Marketing, 19(3), 273–283.

    Google Scholar 

  • Kotha, S., Rajgopal, S., & Rindova, V. (2001). Reputation building and performance: An empirical analysis of the top-50 pure internet firms. European Management Journal, 19(6), 571–586.

    Google Scholar 

  • Kotler, P., & Rackham, N. (2006). Ending the war between sales and marketing. Harvard Business Review, 84, 1–14.

    Google Scholar 

  • Kozlenkova, I. V., Samaha, S. A., & Palmatier, R. W. (2014). Resource-based theory in marketing. Journal of the Academy of Marketing Science, 42, 1–21.

    Google Scholar 

  • Krishnan, H. A., Tadepalli, R., & Park, D. (2009). R&D intensity, marketing intensity, and organizational performance. Journal of Managerial Issues, 21, 232–244.

    Google Scholar 

  • Kristandl, G., & Bontis, N. (2007). Constructing a definition for intangibles using the resource based view of the firm. Management Decision, 45, 1510–1524.

    Google Scholar 

  • Kumar, P. (1999). The impact of long-term client relationships on the performance of business service firms. Journal of Service Research, 2(1), 4–18.

    Google Scholar 

  • Kumar, V. (2016). My reflections on publishing in journal of marketing. Journal of Marketing, 80, 1–6.

    Google Scholar 

  • Kurt, D., & Hulland, J. (2013). Aggressive marketing strategy following equity offerings and firm value: The role of relative strategic flexibility. Journal of Marketing, 77, 57–74.

    Google Scholar 

  • Lee, J., & Chang, Y. B. (2014). Interplay between internal investment and alliance specialization in R&D and marketing. Industrial Marketing Management, 43(5), 813–825.

    Google Scholar 

  • Lee, I. H., & Rugman, A. M. (2012). Firm-specific advantages, inward FDI origins, and performance of multinational enterprises. Journal of International Management, 18(2), 132–146.

    Google Scholar 

  • Lee, J., Sridhar, S., Henderson, C. M., & Palmatier, R. W. (2015). Financial performance effect of customer-centric structure on long-term financial performance. Marketing Science, 34(2), 250–268.

    Google Scholar 

  • Lévesque, M., Joglekar, N., & Davies, J. (2012). A comparison of revenue growth at recent-IPO and established firms: The influence of SG&a, R&D and COGS. Journal of Business Venturing, 27(1), 47–61.

    Google Scholar 

  • Lin, B.-W., Lee, Y., & Hung, S.-C. (2006). R&D intensity and commercialization orientation effects on financial performance. Journal of Business Research, 59(6), 679–685.

    Google Scholar 

  • Lin, C., Tsai, H., & Wu, J. (2014). Collaboration strategy decision-making using the miles and snow typology. Journal of Business Research, 67, 1979–1990.

    Google Scholar 

  • Luo, X. (2008). When marketing strategy first meets wall street: Marketing spendings and firms’ initial public offerings. Journal of Marketing, 72, 98–109.

    Google Scholar 

  • Luo, Y., Zhao, J. H., & Du, J. (2005). The internationalization speed of e-commerce companies: An empirical analysis. International Marketing Review, 22, 693–709.

    Google Scholar 

  • MacKenzie, S. B. (2003). The dangers of poor construct conceptualization. Journal of the Academy of Marketing Science, 31, 323–326.

    Google Scholar 

  • March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2, 71–87.

    Google Scholar 

  • Mhatre, N., Joo, S.-J., & Christopher Lee, C. (2014). Benchmarking the performance of department stores within an income elasticity of demand perspective. Benchmarking: An International Journal, 21(2), 205–217.

    Google Scholar 

  • Mitra, S., & Chaya, A. K. (1996). Analyzing cost-effectiveness of organizations: The impact of information technology spending. Journal of Management Information Systems, 13(2), 29–57.

    Google Scholar 

  • Mittal, V., Anderson, E. W., Sayrak, A., & Tadikamalla, P. (2005). Dual emphasis and the long-term financial impact of customer satisfaction. Marketing Science, 24(4), 544–555.

    Google Scholar 

  • Mizik, N. (2010). The theory and practice of myopic management. Journal of Marketing Research, 47(8), 594–611.

    Google Scholar 

  • Mizik, N., & Jacobson, R. (2007). Myopic marketing management: Evidence of the phenomenon and its long-term performance consequences in the SEO context. Marketing Science, 26(3), 361–379.

    Google Scholar 

  • Moorman, C., & Day, G. S. (2016). Organizing for marketing excellence. Journal of Marketing, 80(6), 6–35.

    Google Scholar 

  • Moorman, C., Du, R., & Mela, C. F. (2005). The effect of standardized information on firm survival and marketing strategies. Marketing Science, 24(2), 263–274.

    Google Scholar 

  • Morgan, N. A., & Rego, L. L. (2009). Brand portfolio strategy and firm performance. Journal of Marketing, 73(1), 59–74.

    Google Scholar 

  • Mottner, S., & Smith, S. (2009). Wal-Mart: Supplier performance and market power. Journal of Business Research, 62(5), 535–541.

    Google Scholar 

  • MSI (2016). 2014–2016 research priorities. Retrieved May 7, 2016, from http://www.msi.org/research/2014-2016-research-priorities/

  • Nair, A., & Selover, D. D. (2012). A study of competitive dynamics. Journal of Business Research, 65(3), 355–361.

    Google Scholar 

  • Nam, H., & Kannan, P. K. (2014). Informational value of social tagging networks. Journal of Marketing, 78(7), 21–40.

    Google Scholar 

  • Narasimhan, O., Rajiv, S., & Dutta, S. (2006). Absorptive capacity in high-technology markets: The competitive advantage of the haves. Marketing Science, 25, 510–524.

    Google Scholar 

  • Nath, P., Nachiappan, S., & Ramanathan, R. (2010). The impact of marketing capability, operations capability and diversification strategy on performance: A resource-based view. Industrial Marketing Management, 39(2), 317–329.

    Google Scholar 

  • Nunnally, J. C. (1978). In R. R. Wright & M. Gardner (Eds.), Psychometric theory. New York: McGraw-Hill.

    Google Scholar 

  • Patwardhan, A. M. (2014). A partial theory of holistic firm-level marketing capability: An empirical investigation. Journal of Management and. Marketing Research, 16(8), 1–46.

    Google Scholar 

  • Peter, J. P. (1981). Construct validity: A review of basic issues and marketing practices. Journal of Marketing Research, 18, 133–145.

    Google Scholar 

  • Porter, M. E. (1985). Competitive advantage. New York: The Free Press.

    Google Scholar 

  • Poston, R., & Grabski, S. (2001). Financial impacts of enterprise resource planning implementations. International Journal of Accounting Information Systems, 2(2), 271–294.

    Google Scholar 

  • Raassens, N., Wuyts, S., & Geyskens, I. (2014). The performance implications of outsourcing customer support to service providers in emerging versus established economies. International Journal of Research in Marketing, 31(3), 280–292.

    Google Scholar 

  • Raithel, S., Sarstedt, M., Scharf, S., & Schwaiger, M. (2012). On the value relevance of customer satisfaction: Multiple drivers and multiple markets. Journal of the Academy of Marketing Science, 40(4), 509–525.

    Google Scholar 

  • Rangan, V. K., & Bell, M. (1998). Dell online. Journal of Interactive Marketing, 12(4), 63–86.

    Google Scholar 

  • Ray, G., Wu, D., & Konana, P. (2009). Competitive environment and the relationship between IT and vertical integration. Information Systems Research, 20(4), 585–603.

    Google Scholar 

  • Rego, L. L., Morgan, N. A., & Fornell, C. (2013). Reexamining the market share-customer satisfaction relationship. Journal of Marketing, 77(9), 1–20.

    Google Scholar 

  • Rugman, A., & Sukpanich, N. (2006). Firm-specific advantages intra-regional sales and performance of multinational enterprises. The International Trade Journal, 20(3), 355–382.

    Google Scholar 

  • Rust, R. T., & Huang, M.-H. (2012). Optimizing service productivity. Journal of Marketing, 76(2), 47–66.

    Google Scholar 

  • Rust, R. T., Ambler, T., Carpenter, G. S., Kumar, V., & Srivastava, R. K. (2004). Measuring marketing productivity: Current knowledge and future directions. Journal of Marketing, 68, 76–89.

    Google Scholar 

  • Sarkees, M. E., & Luchs, R. (2011). Stochastic frontier estimation in international marketing research: Exploring untapped opportunities. Measurement and Research Methods in International Marketing, 22, 99–114.

    Google Scholar 

  • Sarkees, M., Hulland, J., & Chatterjee, R. (2014). Investments in exploitation and exploration capabilities: Balance versus focus. Journal of Marketing, 22, 7–23.

    Google Scholar 

  • Schwertman, N. C., Owens, M. A., & Adnan, R. (2004). A simple more general boxplot method for identifying outliers. Computational Statistics and Data Analysis, 47, 165–174.

    Google Scholar 

  • Selling Power (2016). Selling Power 500 largest sales forces. Retrieved September 23, 2016 from http://www.sellingpower.com/content/article/index.php?a=10505/selling-power-500/largest-sales-forces/2015&page=1/

  • Shapiro, C. (1989). The theory of business strategy. RAND Journal of Economics, 20, 125–137.

    Google Scholar 

  • Shin, N. (1999). Does information technology improve coordination ? An empirical analysis. Logisitcs Information Management, 12(1/2), 138–144.

    Google Scholar 

  • Shin, H. S., Sakakibara, M., & Hanssens, D. M. (2008). Marketing and R&D investment of leader vs. follower. Working Paper, 1–39.

  • Siddharthan, N. S., & Kumar, N. (1990). The determinants of inter-industry variations in the proportion of intra-firm trade: The behaviour of US multinationals. Weltwirtschaftliches Archive, 126(3), 581–591.

    Google Scholar 

  • Snyder, S. (2009). Marketing and R&D complementarity in the pharmaceutical industry. Working Paper, 1–17.

  • Standard and Poor's. (2003). Standard and Poor’s Compustat user’s guide. New York: McGraw-Hill.

    Google Scholar 

  • Standard and Poor's (2013). Standard and Poor’s Compustat user’s guide. Retrieved January 27, 2014 from http://www.batd.eu/debodt/downloads/compustat_user_all.pdf

  • Steiger, J. H. (1980). Tests for comparing elements of a correlation matrix. Psychological Bulletin, 87, 245–251.

    Google Scholar 

  • Swaminathan, V., & Moorman, C. (2009). Marketing alliances, firm networks, and firm value creation. Journal of Marketing, 73(9), 52–69.

    Google Scholar 

  • Tukey, J. W. (1977). Exploratory data analysis. Pearson Education: United States.

    Google Scholar 

  • van Triest, S., Bun, M. J. G., van Raaij, E. M., & Vernooij, M. J. A. (2009). The impact of customer-specific marketing expenses on customer retention and customer profitability. Marketing Letters, 20, 125–138.

    Google Scholar 

  • Varadarajan, R. (2010). Strategic marketing and marketing strategy: Domain, definition, fundamental issues and foundational premises. Journal of the Academy of Marketing Science, 38, 119–140.

    Google Scholar 

  • Vinod, H. D., & Rao, P. M. (2000). R&D and promotion in pharmaceuticals: a conceptual framework and empirical exploration. Journal of Marketing Theory and Practice, 8(4), 10–20, R&D and Promotion in Pharmaceuticals: A Conceptual Framework and Empirical Exploration.

  • Viswanathan, M. (2005). Measurement error and research design. Thousand Oaks: Sage Publications.

    Google Scholar 

  • Vorhies, D. W., Orr, L. M., & Bush, V. D. (2011). Improving customer-focused marketing capabilities and firm financial performance via marketing exploration and exploitation. Journal of the Academy of Marketing Science, 39, 736–756.

    Google Scholar 

  • Wharton (2016). Fundamental annuals data list. Retrieved November 24, 2016 from https://wrds-web.wharton.upenn.edu/wrds/ds/compm/funda/index.cfm?navId=84

  • Wiles, M. A. (2007). The effect of customer service on retailers’ shareholder wealth: The role of availability and reputation cues. Journal of Retailing, 83(1), 19–31.

    Google Scholar 

  • Wuyts, S., Dutta, S., & Stremersch, S. (2004). Portfolios of interfirm agreements in technology-intensive markets: Consequences for innovation and profitability. Journal of Marketing, 68(2), 88–100.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Retailing and Customer Management, University of Cologne, Albertus-Magnus-Platz 1, 50923, Cologne, Germany

    Annette Ptok

  2. Milgard School of Business, University of Washington Tacoma, Tacoma, WA, 98402, USA

    Rupinder P. Jindal

  3. Department of Retailing and Customer Management, Director Center for Research in Retailing, University of Cologne, Albertus-Magnus-Platz 1, 50923, Cologne, Germany

    Werner J. Reinartz

Authors
  1. Annette Ptok
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Rupinder P. Jindal
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Werner J. Reinartz
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Annette Ptok.

Additional information

J. Andrew Petersen served as Area Editor for this article.

Electronic supplementary material

ESM 1

(DOCX 76 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Ptok, A., Jindal, R.P. & Reinartz, W.J. Selling, general, and administrative expense (SGA)-based metrics in marketing: conceptual and measurement challenges. J. of the Acad. Mark. Sci. 46, 987–1011 (2018). https://doi.org/10.1007/s11747-018-0589-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11747-018-0589-2

Keywords

Search

Navigation