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This article provides a high-level overview of marketing strategy research and offers a number of suggestions of areas ripe for future research. We discuss the most fundamental concepts that continue to drive current marketing strategy research and examine how these concepts have shaped marketing strategy and the role of the marketing function. In addition, we highlight the developments in marketing accountability, marketing’s influence within the firm, and alternatives to a market-driven approach in generating sustainable competitive advantage. Finally, we identify directions for future research in the light of recent developments, availability of new data, and emerging issues.

Food is an integral part of everyday life, and food choices directly affect one’s health. Both academics and practitioners have attempted to help consumers make good decisions about their food choices and recommended better or healthier alternatives. However, in thinking about food it is important to put it in context, as each food item is often combined with other food items to create the gestalt of a recipe or meal. Understanding the complex interaction between food items that are used or consumed together is crucial to provide effective recommendations. In this research, I leverage tools from machine learning and textual analysis like the embedding approach for representation learning to understand food in its context and to build recommender systems that account for the complementarity or fit of co-consumed food items. I show that this consideration of fit among food items can lead to better and healthier food recommendations.

In this thesis, we consider two problems in the newsvendor setting with multiple inputs, under a carbon emission constraint and non-linear production functions. In the first problem, we assume a strict carbon cap and find the optimal production quantity and input allocation that will maximize the expected profit under this constraint. In the second problem, we consider an emission trading scheme where an advance purchase of carbon emission permits is made at an initial price before the random demand is realized. When the demand is realized and new carbon trade prices are revealed, it is possible to buy additional permits or to sell an excess amount. The aim is to decide on the optimal allocation of the inputs as well as the carbon trading policy so as to maximize the expected profit. In both problems, the production quantity is linked to multiple inputs via the Cobb-Douglas and Leontief production functions. Optimal policy structures are derived and numerical examples are provided.