We propose a conceptual framework—with the resource-based view (RBV) of the firm as its theoretical underpinning—to explain interfirm differences in firms' profitability in high-technology markets in terms of differences in their functional capabilities. Specifically, we suggest that marketing, R&D, and operations capabilities, along with interactions among these capabilities, are important determinants of relative financial performance within the industry. This paper contributes to the RBV literature by proposing the input-output perspective to conceptualize the notion of capabilities. Specifically, this approach entails modeling a firm's functional activities—viz., marketing, R&D and operations—as transformation functions that relate the productive factors/resources to its functional objectives, if the firm were to deploy these resources most efficiently. Any underattainment of the functional objective, then, is attributable to functional inefficiency, or equivalently, to a lower functional capability of the firm. The input-output conceptualization of a firm's capabilities is then estimated using the stochastic frontier estimation (SFE) methodology. SFE provides the appropriate econometric technique to empirically estimate the efficient frontier and hence the level of efficiency achieved by the various firms. Our study contributes to a number of literatures, both methodologically and substantively. First, it contributes both conceptually and methodologically to the RBV literature. Conceptually, our study suggests that firm capabilities can be viewed in an input–output framework. Methodologically, the study suggests the use of stochastic frontier estimation to operationalize and estimate firm capabilities. This methodology is, to the best of our knowledge, the first to allow the researcher/manager to capabilities from archival data. Substantively, our study contributes to the literature on market orientation by suggesting that a stronger market orientation of a firm should be reflected in a higher marketing capability. It also adds to the literature on “design for manufacturability” by explicating the complementarity among the various functional capabilities and offering empirical evidence on their relative importance in influencing a firm's performance. Finally, our study builds on prior literature that has highlighted the importance of marketing–R&D coordination as important determinants of new product development and success. We highlight below some of our main findings. • A strong base of innovative technologies enhances a firm's sales by favorably influencing consumers' expectations about the externality benefits associated with its product. This suggests that a past track record of consistent innovation is a credible signal to current and potential customers of the firm's continued excellence in a technologically evolving market. Given the importance of influencing customers, managers need to tailor their marketing activities around the need to inform customers of the technological excellence of their firm...

This paper attempts to operationalize and measure firm-specific capabilities using an extant conceptualization in the resource-based view (RBV) literature. Capabilities are conceived as the efficiency with which a firm employs a given set of resources (inputs) at its disposal to achieve certain objectives (outputs). We expand on extant theoretical literature on relative capabilities, by delineating the conditions that have to be met for relative capabilities to be measured non-tautologically. We then proceed to suggest an estimation methodology, stochastic frontier estimation (SFE), that allows us to infer

The rapid rate of knowledge obsolescence in many high-technology markets makes it imperative for firms to renew their technological bases constantly. Given its critical importance, excellence in renewal of technological base would serve as a . Drawing on past literature, we identify this dynamic capability associated with acquiring and utilizing external technological know-how with the notion of (AC). We ask the following questions: (a) What would cause some firms to have a higher AC than others? and, (b) What is the impact of AC on a firm's profitability? We build a conceptual framework suggesting that marketing, R&D, and operations capabilities have a significant positive impact on a firm's AC. We test our framework on a data set of firms in high-technology markets. Using an econometric technique called stochastic frontier estimation, we the AC of firms from an observation of the know-how they actually absorb. We find that firm-specific capabilities significantly impact AC. Also, we find that AC has a significant impact on profitability and that this impact is moderated by the pace of technological change: the greater the pace of change, the greater the impact.absorptive capacity, dynamic capabilities, high-technology markets, resource-based view, marketing capability, organizational learning, knowledge acquisition

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Prior behavioral research has suggested that advertising can influence a consumer's quality evaluation through informative and transformative effects. The informative effect acts directly to inform a consumer of product attributes and hence shapes her evaluations of brand quality. The transformative effect affects the consumer's evaluation of brand quality by enhancing her assessment of her subsequent consumption experience. In addition, advertising may influence a consumer's utility directly, even without providing any explicit information—this is the persuasive effect. In this paper, we propose a framework that formally models the processes through which all three effects of advertisements impact consumers' brand evaluations and their subsequent brand choice decisions. In particular, we model source credibility, confirmatory bias, and bounded rationality on the part of consumers, by appropriately modifying the standard Bayesian learning approach. Our model conforms closely to prior behavioral literature and the experimental findings therein. In our empirical analysis, we get significant estimates of both informative and transformative effects across brands. We find interesting temporal patterns across the effects; for instance, the importance of transformative effects seem to grow over time, while that of informative effects diminishes. Finally, we conduct policy experiments to examine the impact of increased ad intensity on advertising effects, as well as the role played by consumption ambiguity.advertising effects, informative effects, persuasive effects, structural models, consumer learning, policy experiments, bounded rationality, confirmatory bias