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Ordinary capabilities and firm performance: The role of capital market development

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Abstract

Organizational capabilities have a key influence on firm performance. Ordinary capabilities, a prominent classification advocated by capability scholars, allow a firm to perform its primary functional activities. Past research indicates that there are limits to the contributions of ordinary capabilities to firm performance, but largely has explored it via contingent effects in an industry context. We argue, however, that these limits also are a function of the development of market-supporting institutions. In this paper, we investigate the effect of capital market development – a key pillar of market-supporting institutions – on a firm’s use of two ordinary capabilities, operations and marketing. We trace the heterogeneity of this effect for two key firm resources, investments in R&D and financial slack, that are indicative of different strategies pursued by firms. We test our three-way interaction model using a sample of Indian firms over a twenty-year period of institutional reforms. Our findings contribute to integrating the organizational capability and institutional theory literature and advancing research on the sustainability of firm profits in emerging economies.

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Authors and Affiliations

  1. Indian Institute of Management Kozhikode, Kozhikode, Kerala, 673570, India

    Nycil George & Anita Kerai

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  1. Nycil George
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  2. Anita Kerai
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Correspondence to Nycil George.

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Appendix

Appendix

Table 5 Major economies around the world
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A2. DEA Illustration: Marketing capability

To illustrate our estimation of marketing capability using DEA, we include the following snippet from our sample.

Table 6 Data snippet
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A, B, C, and D are four firms (names disguised) in the same industry. As shown in Table 6 above, in the year 2018 these firms had varying levels of sales (output variable), incurred different amounts of marketing expenditure, and differed in their accounts of intangible assets and trade receivables (the three input variables). It was not easy to directly estimate which among the four firms were more efficient in their sales for the varying efforts that they had put in because the weights for the input variables are not known. Further, these weights would vary for different industry and year combinations.

DEA allows us to calculate an efficiency score for each firm in a given group. We classified firms into groups based on each industry-year combination. The efficiency score was calculated using linear programming by maximizing the ratio of weighted average of output(s) to the weighted average of inputs such that each firm was assigned the best set of weights, i.e., the efficiency score was maximized for each firm, with weights being non-negative. The maximum allowed efficiency is 1, or 100%.

This allows each firm’s efficiency score to be calculated based on differences in how they choose to use various inputs, i.e., differences in their underlying strategies or use of marketing capabilities, and yet the standardization allows comparability across firms (Ahmed et al., 2014).

For a simple case of one input and output, the calculated efficiency frontier can be depicted as shown in Fig. 

Fig. 7
figure 7

DEA illustration

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7. Firms lying on the efficiency frontier are assigned the maximum efficiency score of 1. All other firms are given a score depending on their distance from the efficiency frontier. The greater the distance from the frontier, the lower the score of a given firm.

Table 7 Random-effects regression of firm performance on operations capability
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Table 8 Random-effects regression of firm performance on marketing capability
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Table 9 Fixed-effects regression of firm performance on operations capability: Sample of only manufacturing firms
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Table 10 Fixed-effects regression of firm performance on marketing capability: Sample of only manufacturing firms
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Table 11 Fixed-effects regression of firm performance on operations capability: Additional institutional development controls
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Table 12 Fixed-effects regression of firm performance on marketing capability: Additional institutional development controls
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Table 13 Dynamic panel regression (two-step estimation) of firm performance on operations and marketing capability
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George, N., Kerai, A. Ordinary capabilities and firm performance: The role of capital market development. Asia Pac J Manag 41, 233–274 (2024). https://doi.org/10.1007/s10490-022-09848-3

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