The global population is expected to reach 10.5 billion by 2050. With the increase in population, food production needs to increase by at least 70% in 2050. This would require a several-fold increase in food production. However, scarcity in land availability, a falling water table, weather variability, and an increase in the cost of agricultural operations have made this difficult. The gap between food supply and demand could be minimized if food losses are reduced during production, post-harvest activities, and food waste during consumption. This dissertation focuses on food loss (FL) by growers and food-waste (FW) by households. Specifically, the dissertation first, investigates the impact of vertical coordination on FL in India. Secondly, the dissertation examines the impact of offline and online shopping on FW by American households. The FL study uses farm-level data from India and a novel estimation method in the literature. Findings show that agribusiness firms rejected a significant quantity of the product due to quality standards. The amount of produce rejected was directly impacted by labor and transportation costs. Modeling and simulating the effects of labor and transport costs show that lowering labor and transport costs for the smallholder growers would reduce FL. The FW study uses scanner data of a popular retailing chain in the United States. Using the behavior of over-purchasing of impulse products and machine learning approach, the predict the over-purchasing of impulse products across online and offline (grocery stores) channels. The study finds that households over-purchase 29% more of impulse products (danish pastries, sweet bread, and cakes) when shopping online compared to offline shopping. The dissertation provides two critical insights related to the decision-making process of growers and grocery shoppers. First, growers' decision on reducing FL is related to the quantity of produce rejected by contracting firms and selling produce in the spot markets. Second, FW is significantly related to a grocery shopper’s choice of a shopping channel and the decision on how much to purchase.

Consumers can purchase local food through intermediated marketing channels, such as grocery stores, or through direct-to-consumer marketing channels, for instance, farmers markets. While the number of farms that utilize direct-to-consumer outlets keeps increasing, the direct-to-consumer sales remain lower than intermediated sales. If consumers prefer to purchase local food through intermediated channels, then policies designed to support direct channels may be misguided. Using a variety of experiments, this dissertation investigates consumer preferences for local food and their demand differentiated by marketing channel. In the first essay, I examine the existing literature on consumer preferences for local food by applying meta-regression analysis to a set of eligible research papers. My analysis provides evidence of statistically significant willingness to pay for local food products. Moreover, I find that a methodological approach and study-specific characteristics have a significant influence on the reported estimates for local attribute. By separating the demand for local from the demand for a particular channel, the second essay attempts to disentangle consumers’ preferences for marketing channels and the local-attribute in their food purchases. Using an online choice experiment, I find that consumers are willing to pay a premium for local food. However, they are not willing to pay premiums for local food that is sold at farmers markets relative to supermarkets. Therefore, in the third essay I seek to explain the rise in intermediated local by investigating local food shopping behavior. I develop a model of channel-selection in a nested context and apply it to the primary data gathered through an online food diary. I find that, while some consumers enjoy shopping at farmers markets to meet their objectives, such as socialization with farmers, the majority of consumers buy local food from supermarkets because they offer convenient settings where a variety of products can be bought as one basket. My overall results suggest that, if the goal is to increase the sales of local food, regardless of the channel, then existing supply-chain relationships in the local food channel appear to be performing well.

Private label growth in emerging markets has not kept pace with the growth in private labels elsewhere. For instance, in Europe and North America, private labels now constitute an average of 35% of total retail market share, compared to emerging markets, where market shares vary between 1% and 8 %. This dissertation examines the possibility that differences in private-label performance between developed and emerging economies is not driven by one mechanism, but arises from a variety of sources, both structural, and behavioral. Specifically, I focus on manufacturers’ market power, retailers’ private label portfolio strategies, and consumers’ perceptions of private labels. In most emerging economies, national brand manufacturers tend to be the sole producers of private labels. As a result, manufacturers have inherent market power and can deter retailers from pursuing aggressive private label strategies, which results in low private label market shares. Moreover, some retailers in emerging economies now carry their private labels as part of a multi-tiered portfolio. However, a small price-gap between the quality tiers results in high intraportfolio competition leading to cannibalization and lower private label market shares. Last, private label market shares in emerging economies may be smaller than in developed economies because low-income households prefer higher priced national brands. This counterintuitive phenomenon is driven by two interrelated factors. First, social influence implies that low-income households are upward-comparing, they contrast themselves with high-income households whom they believe are better-off. Because higher-income households purchase national brands, upward-comparisons lead to a preference for national brands. Second, low income households are unknowledgeable about private label advancements hence they prefer national brands.

It is well understood that innovation drives productivity growth in agriculture. Innovation, however, is a process that involves activities distributed throughout the supply chain. In this dissertation I investigate three topics that are at the core of the distribution and diffusion of innovation: optimal licensing of university-based inventions, new variety adoption among farmers, and consumers’ choice of new products within a social network environment.

University researchers assume an important role in innovation, particularly as a result of the Bayh-Dole Act, which allowed universities to license inventions funded by federal research dollars, to private industry. Aligning the incentives to innovate at the university level with the incentives to adopt downstream, I show that non-exclusive licensing is preferred under both fixed fee and royalty licensing. Finding support for non-exclusive licensing is important as it provides evidence that the concept underlying the Bayh-Dole Act has economic merit, namely that the goals of university-based researchers are consistent with those of society, and taxpayers, in general.

After licensing, new products enter the diffusion process. Using a case study of small holders in Mozambique, I observe substantial geographic clustering of new-variety adoption decisions. Controlling for the other potential factors, I find that information diffusion through space is largely responsible for variation in adoption. As predicted by a social learning model, spatial effects are not based on geographic distance, but rather on neighbor-relationships that follow from information exchange. My findings are consistent with others who find information to be the primary barrier to adoption, and means that adoption can be accelerated by improving information exchange among farmers.

Ultimately, innovation is only useful when adopted by end consumers. Consumers’ choices of new products are determined by many factors such as personal preferences, the attributes of the products, and more importantly, peer recommendations. My experimental data shows that peers are indeed important, but “weak ties” or information from friends-of-friends is more important than close friends. Further, others regarded as experts in the subject matter exert the strongest influence on peer choices.

Private labels command a growing share of food retailers' shelf space. In this dissertation, I explain this phenomenon as resulting from "umbrella branding," or the ability of a single brand to reach across categories. Conceptually, I define umbrella branding as a behavioral attribute that describes a shopper's tendency to ascribe a performance bond to a brand, or to associate certain performance characteristics to a private label brand, across multiple categories. In the second chapter, I describe the performance bond theory in detail, and then test this theory using scanner data in the chapter that follows. Because secondary data has limitations for testing behavioral theories, however, I test the performance bond theory of umbrella branding using a laboratory experiment in the fourth chapter. In this chapter, I find that households tend to transfer their perception of private label performance across categories, or that a manifestation of umbrella branding behavior can indeed explain private labels' success. In the fifth chapter, I extend this theory to compare umbrella branding in international markets, and find that performance transference takes its roots in consumers' cultural backgrounds. Taken together, my results suggest that umbrella branding is an important behavioral mechanism, and one that can be further exploited by retailers across any consumer good category with strong credence attributes.

It is well understood that decisions made under uncertainty differ from those made without risk in important and significant ways. Yet, there is very little research into how uncertainty manifests itself in the most ubiquitous of decision-making environments: Consumers' day-to-day decisions over where to shop, and what to buy for their daily grocery needs. Facing a choice between stores that either offer relatively stable "everyday low prices" (EDLP) or variable prices that reflect aggressive promotion strategies (HILO), consumers have to choose stores under price-uncertainty. I find that consumers' attitudes toward risk are critically important in determining store-choice, and that heterogeneity in risk attitudes explains the co-existence of EDLP and HILO stores - an equilibrium that was previously explained in somewhat unsatisfying ways. After choosing a store, consumers face another source of risk. While knowing the quality or taste of established brands, consumers have very little information about new products. Consequently, consumers tend to choose smaller package sizes for new products, which limits their exposure to the risk that the product does not meet their prior expectations. While the observation that consumers purchase small amounts of new products is not new, I show how this practice is fully consistent with optimal purchase decision-making by utility-maximizing consumers. I then use this insight to explain how manufacturers of consumer packaged goods (CPGs) respond to higher production costs. Because consumers base their purchase decisions in part on package size, manufacturers can use package size as a competitive tool in order to raise margins in the face of higher production costs. While others have argued that manufacturers reduce package sizes as a means of raising unit-prices (prices per unit of volume) in a hidden way, I show that the more important effect is a competitive one: Changes in package size can soften price competition, so manufacturers need not rely on fooling consumers in order to pass-through cost increases through changes in package size. The broader implications of consumer behavior under risk are dramatic. First, risk perceptions affect consumers' store choice and product choice patterns in ways that can be exploited by both retailers and manufacturers. Second, strategic considerations prevent manufacturers from manipulating package size in ways that seem designed to trick consumers. Third, many services are also offered as packages, and also involve uncertainty, so the effects identified here are likely to be pervasive throughout the consumer economy.

I compare the effect of anonymous social network ratings (Yelp.com) and peer group recommendations on restaurant demand. I conduct a two-stage choice experiment in which restaurant visits in the first stage are informed by online social network reviews from Yelp.com, and visits in the second stage by peer network reviews. I find that anonymous reviewers have a stronger effect on restaurant preference than peers. I also compare the power of negative reviews with that of positive reviews. I found that negative reviews are more powerful compared to the positive reviews on restaurant preference. More generally, I find that in an environment of high attribute uncertainty, information gained from anonymous experts through social media is likely to be more influential than information obtained from peers.

Consumers search before making virtually any purchase. The notion that consumers engage in costly search is well-understood to have deep implications for market performance. However to date, no theoretical model allows for the observation that consumers often purchase more than a single product in an individual shopping occasion. Clothing, food, books, and music are but four important examples of goods that are purchased many items at a time. I develop a modeling approach that accounts for multi-purchase occasions in a structural way. My model shows that as preference for variety increases, so does the size of the consideration set. Search models that ignore preference for variety are, therefore, likely to under-predict the number of products searched. It is generally thought that lower search costs increase retail competition which pushes prices and assortments down. However, I show that there is an optimal number of products to offer depending on the intensity of consumer search costs. Consumers with high search costs prefer to shop at a store with a large assortment of goods and purchase multiple products, even if the prices that firm charges is higher than competing firms' prices. On the other hand, consumers with low search costs tend to purchase fewer goods and shop at the stores that have lower prices, as long as the store has a reasonable assortment offering. The implications for market performance are dramatic and pervasive. In particular, the misspecification of demand model in which search is important and/or multiple discreteness is observed will produce biased parameter estimates leading to erroneous managerial conclusions.

The lack of food safety in a grower's produce presents the grower with two risks; (1) that an item will need to be recalled from the market, incurring substantial costs and damaging brand equity and (2) that the entire market for the commodity becomes impaired as consumers associate all produce as being risky to eat. Nowhere is this more prevalent than in the leafy green industry, where recalls are relatively frequent and there has been one massive E. coli outbreak that rocked the industry in 2006. The purpose of this thesis is to examine insurance policies that protect growers from these risks. In doing this, a discussion of current recall insurance policies is presented. Further, actuarially fair premiums for catastrophic revenue insurance policies are priced through a contingent claims framework. The results suggest that spinach industry revenue can be insured for $0.02 per carton. Given the current costs of leafy green industry food safety initiatives, growers may be willing to pay for such an insurance policy.