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Market-based capabilities and financial performance of firms: insights into marketing’s contribution to firm value

  • Original Empirical Research
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Abstract

While there is recognition that market-based capabilities contribute to a firm’s financial performance, the exposition is largely conceptual (Srivastava et al. Journal of Marketing 62:2–18, 1998; Journal of Marketing 63:168–179, 1999). Using a resource based view of the firm, the present study proposes that (1) market-based assets and capabilities of a firm impacts (2) performance in three market-facing business processes (new product development, supply-chain and customer management), which in turn, influence (3) the firm’s financial performance. It develops related hypotheses and tests the framework empirically. The study also examines for the first time the interrelationship among the three business processes and their impact on the market value of firms. Further, the study examines the moderating influence of two organizational variables—size and age of the firm. Overall, the major contribution of the study is that it offers a process linkage between capabilities, process performance and financial performance. The results of this research will provide strategic insights to managers on optimal customer management, product development and supply chain strategies.

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Notes

  1. We believe that marketing is likely to influence all three cross-functional business processes (NPD, SCM and CM) within the organization by the impact it has on MBCs. This approach is different from other work that relates the function directly to firm performance.

  2. Our study is somewhat different from other CM studies that have focused primarily on organizational determinants of CM performance. Some of the organizational factors identified in other studies include culture, cross-functional integration, management commitment, user participation, and training. We believe that these organizational determinants will eventually impact CM performance by their effect on organizational ability to execute customer-related activities like the ones used in our study. For example, management commitment could result in (a) greater CM investments, (b) greater authority for CM implementers, and (c) greater coordination across business functions. These however will impact organizational ability to respond effectively to customer needs and treatment of customers as internal assets rather than as external entities (which are the determinants used in our study).

  3. Active consideration was given for using the marketing orientation concept (Kohli and Jaworski 1990) to explain differences in CM performance across firms. However, because the CM literature prescribes a much broader set of determinants, the same was used in developing the study hypotheses.

  4. R&D Intensity is used as a covariate in the NPD process part of the model. It is typically defined as the proportion of annual sales that is spent on research and development. As pointed out by a reviewer, this measure is useful within an industry, but can be misleading in cross-sectional comparisons (an R&D/sales ratio may be low within a particular industry but look high compared to firms from other industries). A new R&D intensity index was therefore created by computing a multiplicative term that is based on (a) a firm’s R&D score indexed by the average R&D score in its SIC group, and (b) a firm’s R&D score indexed by the overall mean for the entire sample of firms. The first component captures whether a firm’s R&D score is smaller or bigger than the average in its industry; and the second component captures where a firm is across the entire sample of firms.

  5. These items/dimensions are similar to the measures used by Baker and Sinkula (2005) for capturing new product success of a firm. Baker and Sinkula (2005) include new product rate (number of new products in the present study), new product success rate (products that are market winners in the present study), degree of product differentiation (NPD-DP), competitors’ ability to copy new products (NPD-DP) and new product cycle time (NPD-TE).

  6. Additionally, objective financial performance metrics—profitability (EBIT), sales, and market value—were collected from Compustat tapes for the time period 1997–2004. The data collection year (2001) was used as a separation point and average performance was computed for the four years before 2001 (1997–2000) and three years after 2001 (2002–2004). These average numbers were used to compute a growth index for each objective indicator. Additionally, the price to book ratio was computed for each firm for the time period 2002 to 2004. We were however limited in gathering objective data for all firms in the sample as many were privately-held. Objective data was collected only for 51 of the 88 firms in the sample. The model captured the direct and indirect effect of process performance variables on firm performance. The indirect effect is based on the notion that the impact of business processes will be felt first on revenue and profit growth of the firm; these, in turn, will likely enable investors providing a higher price multiple for such firms. Results showed that CM performance influenced both price-to-book ratio and growth in market value indirectly through its positive impact on sales growth. SCM performance influenced price-to-book ratio directly in a positive manner. NPD performance had no impact on any of the objective performance indicators. Overall, these results are quite consistent with the findings for subjective financial performance.

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Acknowledgment

The authors thank the Marketing Science Institute for providing support and funding for the study.

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Authors and Affiliations

  1. Iowa State University, Ames, IA, USA

    Sridhar N. Ramaswami

  2. Provost and VP for Academic Affairs, Singapore Management University and Roberto C. Goizueta Chair in Marketing and e-Commerce, Emory University, Singapore, Singapore

    Rajendra K. Srivastava

  3. Oakland University, Oakland, MI, USA

    Mukesh Bhargava

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  1. Sridhar N. Ramaswami
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  2. Rajendra K. Srivastava
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Correspondence to Sridhar N. Ramaswami.

Appendix: measures

Appendix: measures

This section includes measures for constructs not included in Table 2. A five-point strongly disagree–strongly agree scale is used for the first two scales below.

New product development performance-differentiated products (NPD-DP)

  • Our products are difficult for competition to copy.

  • Our product designs are unique.

  • Our products do not have a significant advantage over those of competitors. [R]

New product development performance-time efficiency (NPD-TE)

  • In general, we have difficulty adhering to time deadlines in our new product projects. [R]

  • We get our products to market on or ahead of schedule.

  • We perform better than our objectives on speed of new product development.

The following stem is used for the next four measures. (1 = worse, 4 = on par, and 7 = better)

Relative to your firm’s (division’s) stated objectives, how is your firm (division) performing on:

New product development performance-outcomes (NPD-OS)

  • Number of new products developed

  • Number of new products that are “big” winners

Customer management performance (PCM)—adapted from Moorman and Rust (1999)

  • Customer satisfaction

  • Customer retention

  • Ability to charge price premium for products/services

  • Increasing number of relationships with customers through cross-selling

  • Image/reputation

Supply chain management performance (PSCM)—new scale

  • Inventory cost

  • Implementing JIT processes

  • Smoothing demand volatility

Financial performance—adapted from Moorman and Rust (1999)

  • Sales

  • Profitability

  • Market share

  • Net operating margins

  • Return on assets

R&D intensity (adjusted to industry norms)

What is your annual R&D expenditures as a percentage of sales?

(<1%, 1–3%, 4–6%, 7–9%, 10–12%, 13–15%, >15%)

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Ramaswami, S.N., Srivastava, R.K. & Bhargava, M. Market-based capabilities and financial performance of firms: insights into marketing’s contribution to firm value. J. of the Acad. Mark. Sci. 37, 97–116 (2009). https://doi.org/10.1007/s11747-008-0120-2

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