Big data and predictive analytics for supply chain and organizational performance

With big data growing rapidly in importance over the past few years, academics and practitioners have been considering the means through which they can incorporate the shifts these technologies bring into their competitive strategies. To date, emphasis has been on the technical aspects of big data, with limited attention paid to the organizational changes they entail and how they should be leveraged strategically. As with any novel technology, it is important to understand the mechanisms and processes through which big data can add business value to companies, and to have a clear picture of the different elements and their interdependencies. To this end, the present paper aims to provide a systematic literature review that can help to explain the mechanisms through which big data analytics (BDA) lead to competitive performance gains. The research framework is grounded on past empirical work on IT business value research, and builds on the resource-based view and dynamic capabilities view of the firm. By identifying the main areas of focus for BDA and explaining the mechanisms through which they should be leveraged, this paper attempts to add to literature on how big data should be examined as a source of competitive advantage. To this end, we identify gaps in the extant literature and propose six future research themes.

/pdf/big-data-analytics-capabilities-a-systematic-literature-1l761jqxu3.pdf

Big data analytics capabilities: a systematic literature review and research agenda

Assessing business value of Big Data Analytics in European firms

Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities

With big data analytics growing rapidly in popularity, academics and practitioners have been considering the means through which they can incorporate the shifts these technologies bring into their competitive strategies. Drawing on the resource‐based view, the dynamic capabilities view, and on recent literature on big data analytics, this study examines the indirect relationship between a big data analytics capability (BDAC) and two types of innovation capabilities: incremental and radical. The study extends existing research by proposing that BDACs enable firms to generate insight that can help strengthen their dynamic capabilities, which in turn positively impact incremental and radical innovation capabilities. To test their proposed research model, the authors used survey data from 175 chief information officers and IT managers working in Greek firms. By means of partial least squares structural equation modelling, the results confirm the authors’ assumptions regarding the indirect effect that BDACs have on innovation capabilities. Specifically, they find that dynamic capabilities fully mediate the effect on both incremental and radical innovation capabilities. In addition, under conditions of high environmental heterogeneity, the impact of BDACs on dynamic capabilities and, in sequence, incremental innovation capability is enhanced, while under conditions of high environmental dynamism the effect of dynamic capabilities on incremental innovation capabilities is amplified.

/pdf/big-data-analytics-capabilities-and-innovation-the-mediating-3okr0566i9.pdf

Big Data Analytics Capabilities and Innovation: The Mediating Role of Dynamic Capabilities and Moderating Effect of the Environment

Big Data consumer analytics and the transformation of marketing

A content analysis of 814 advertisements from three major television networks was conducted to assess the representation and role portrayal of senior citizens in television advertising. While 12 percent of the current U.S. population is over 65 years of age, only seven percent of the advertisements containing people utilized elderly characters. In the majority of commercials, the elderly are not typically cast in major roles, but instead appear most often in home settings with members of other age groups present. In those advertisements where older persons are portrayed as major role advisors about a product or service, the advisor is likely to be male.

The Portrayal of Older Americans in Television Commercials

Little is known about the sales effects of different aged models on older (65 years and over) and younger (less than 65 years) consumers. This is an important issue because marketers have expressed some fear about using older models in the promotion of products directed at multiple age groups. This article presents the results of a study of 3,390 consumers' sales response to older, younger, and a combination of older and younger models in point-of-purchase advertising for an age-free product. The results indicate that model age does not have a significantly different effect on consumers of different ages. Managerial implications are provided

Will Older Models Turn Off Shoppers

The purpose of this article is to extend latitudinally the stream of research regarding racial minorities in industrial advertising and to provide a benchmark for future longitudinal studies. It utilizes content analysis to examine business-to-business direct mail advertising depiction of African-Americans. Findings indicate that about 28 percent of the direct mail pieces depicted blacks, nearly six percent of all people portrayed were African-American, there was virtually no difference in occupational portrayals of blacks and whites, and blacks were most frequently portrayed separately from whites. Implications of these findings for users of industrial direct mail are discussed.

Linda E. Swayne

Papers

Big Data consumer analytics and the transformation of marketing

The Portrayal of Older Americans in Television Commercials

Will Older Models Turn Off Shoppers

The Portrayal of African-Americans in Business-To-Business Direct Mail: A Benchmark Study

Contribution of southern authors in major marketing publications