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While Big Data offer marketing managers information that is high in volume, variety, velocity, and veracity (the 4Vs), these features wouldn’t necessarily improve their decision-making. Managers would still be vulnerable to confirmation bias, control illusions, communication problems, and confidence issues (the 4Cs). The authors argue that traditional remedies for such biases don’t go far enough and propose a lean start-up approach to data-based learning in marketing management. Specifically, they focus on the marketing analytics component of Big Data and how adaptations of the lean start-up methodology can be used in some combination with such analytics to help marketing managers improve their decision-making and innovation process. Beyond the often discussed technical obstacles and operational costs associated with handling Big Data, this chapter contributes by analyzing the various learning and decision-making problems that can emerge once the 4Vs of Big Data have materialized.

The extant international service marketing literature focuses heavily on the impact of globalization on the outward process of the internationalization of service firms. The purpose of this paper is to propose scholars examine international service marketing from a different perspective, that of the globalization of domestic markets and the existence of global segments throughout the world.

The paper uses resource‐advantage theory and a congruence approach to suggest that the alignment of resources with consumer needs in the globalized domestic market leads to competitive advantage for the firm.

It can be argued that this alignment will lead to the replication of the competitive advantage across global segments in expansion to new markets.

The paper provides two significant contributions to the literature: a new perspective for considering the globalization of services that incorporates the challenges of operating in globalized markets; and develops seven propositions that can serve as a foundation for a stream of research on the globalization of services.

We examine the citations from four international business (IB) journals over 2000‐2004 to show the areas, the journals, and the institutions that impact IB research. The leading works that influence IB research are primarily management journals, scholarly books, and IB journals. IB research is published in non‐IB journals, as well and this has influenced the recent research in IB journals. U.S. and non‐U.S. academic institutions and non‐academic organizations are among the top 100 institutions that impact IB research, indicating that this research is a truly global endeavor. Finally, recent IB research is influenced more by recent published research than by past research. Scholarly books have become less influential, while the economics, finance, and marketing journals show no change in the influence on IB research over time.

Structural equation modeling (SEM) is a powerful multivariate statistical technique that requires careful application. The use of SEM in international business research has substantially increased recently, necessitating a critical evaluation of its use in the field. Through an analysis of 148 articles in the international business (IB) literature, we detail the state of current use of SEM in IB research and compare its use to the established best practices. In many instances, SEM's use in IB has been faulty, suggesting that authors may have drawn incorrect conclusions. To expand the IB field's knowledge base, methodological accuracy is essential. Based on our review of the technique's use in IB research coupled with the established practices in the social science literature, we provide practical suggestions for better applying SEM in the IB literature.

We searched JM from 1990 to 2005 to identify all studies that employed OLS regression.¹ The search resulted in 83 articles with 147 OLS regressions. Many authors specifically state that they used OLS and these were promptly included in the sample. Other authors acknowledged regression as a methodological procedure without explicitly specifying an estimation technique. To inquire whether OLS was used, we communicated with all of these authors. In all, 51 authors were contacted, with 44 responding. Of the 44 that responded 43 had used OLS; the only exception was subsequently excluded from the analysis. The remaining seven articles were checked once more, and consensus was reached that OLS had most likely been used. Therefore, they were also included in the study.