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This article examines how smallholders in Oaxaca, Mexico, experienced and responded to the recent coffee rust disaster, asking whether fair trade coffee producer organizations helped smallholders develop coping mechanisms to offset their vulnerability. It demonstrates how Oaxacan coffee producers were especially vulnerable during the recent rust outbreak due to long-term trends including a decline in governmental support for the sector dating back to the 1990s which resulted in a decline in producer incomes and a concomitant rise in the number of aging and poorly managed coffee plots that were more susceptible to coffee rust. The ongoing price volatility within coffee commodity markets and the continued restructuring of the specialty coffee market also increases the uncertainty producers face when determining how to best respond to the rust disaster. The article details the concrete ways in which fair trade coffee producer organizations help bolster the adaptive capacity of their members, while also noting areas for improvement.

Companies in all industries are searching for new sources of competitive advantage since the competition in their marketplace is becoming increasingly intensive. The resource-based view of the firm explains the sources of sustainable competitive advantages. From a resource-based view perspective, relational based assets (i.e., the assets resulting from firm contacts in the marketplace) enable competitive advantage. The relational based assets examined in this work are brand image and corporate reputation, as components of brand equity, and customer value. This paper explores how they create value. Despite the relatively large amount of literature describing the benefits of firms in having strong brand equity and delivering customer value, no research validated the linkage of brand equity components, brand image, and corporate reputation, simultaneously in the customer value–customer loyalty chain. This work presents a model of testing these relationships in consumer goods, in a business-to-business context. The results demonstrate the differential roles of brand image and corporate reputation on perceived quality, customer value, and customer loyalty. Brand image influences the perception of quality of the products and the additional services, whereas corporate reputation actions beyond brand image, estimating the customer value and customer loyalty. The effects of corporate reputation are also validated on different samples. The results demonstrate the importance of managing brand equity facets, brand image, and corporate reputation since their differential impacts on perceived quality, customer value, and customer loyalty. The results also demonstrate that companies should not limit to invest only in brand image. Maintaining and enhancing corporate reputation can have a stronger impact on customer value and customer loyalty, and can create differential competitive advantage.

Many dynamic problems in economics are characterized by large state spaces which make both computing and estimating the model infeasible. We introduce a method for approximating the value function of high-dimensional dynamic models based on sieves and establish results for the (a) consistency, (b) rates of convergence, and (c) bounds on the error of approximation. We embed this method for approximating the solution to the dynamic problem within an estimation routine and prove that it provides consistent estimates of the modelik’s parameters. We provide Monte Carlo evidence that our method can successfully be used to approximate models that would otherwise be infeasible to compute, suggesting that these techniques may substantially broaden the class of models that can be solved and estimated.

Like language, the law is an instrument – a tool – for the accomplishment of certain purposes. The idealized understanding insisted that the law is, if not divinely inspired, the empirical manifestation of received wisdom and truth. On this view the law is crafted to produce ideal outcomes. Richard Posner once insisted that the law was purposefully crafted to achieve economic efficiency (1973).¹ Warren Samuels reminded us that the law is an instrument to get one's way. The interesting question, therefore, concerns who is able to control this valuable instrument? Sometimes good and noble people wield the tool. At other times nefarious forces prevail. Samuels presented his vision of the law by means of a Virginia statute concerning an obscure pest known as Cedar Rust (Samuels, 1971). As it happens, Virginia apple growers were able to wield the tool – saws and axes – against red cedar trees which serve as an intermediate host for a fungus detrimental to apple trees. Small spores make for large debates.

This chapter provides an overview of the strategic implications of chatbot use and implementation, including potential applications in marketing, and factors affecting customer acceptance. After presenting a brief history and a classification of conversational artificial intelligence (AI) and chatbots, the authors provide an in-depth review at the crossroads between marketing, business, and human–computer interaction, to outline the main factors that drive users' perceptions and acceptance of chatbots. In particular, the authors describe technology-related factors and chatbot design characteristics, such as anthropomorphism, gender, identity, and emotional design; context-related factors, such as the product type, task orientation, and consumption contexts; and users-related factors such as sociodemographic and psychographic characteristics. Next, the authors detail the strategic importance of chatbots in the field of marketing and their impact on consumers' perceived service quality, satisfaction, trust, and loyalty. After discussing the ethical implications related to chatbots implementation, the authors conclude with an exploration of future opportunities and potential strategies related to new generative AI technologies, such as ChatGPT. Throughout the chapter, the authors offer theoretical insights and practical implications for incorporating conversational AI into marketing strategies.

The purpose of this research was an attempt to improve the applicability of the balance scorecard, in particular the customer perspective, in the hospitality industry. The objective of the study was to investigate a more structured customer-centric performance measurement framework customized for the hotel industry. Hence, this paper presents the “Customer Calculator” which had been developed based on the Customer Equity model proposed by Rust et al. (2000a). Qualitative examinations by interviewing hotel management were conducted to test the applicability of the customer-centric measurement framework. The customer scores facilitate hotel decision-makers who can pinpoint the important drivers of customer relations, which are in need of further action and improvement. The framework can also be employed by the stakeholders to assess hotel performance in general.

We derive marginal conditions of optimality (i.e., Euler equations) for a general class of Dynamic Discrete Choice (DDC) structural models. These conditions can be used to estimate structural parameters in these models without having to solve for approximate value functions. This result extends to discrete choice models the GMM-Euler equation approach proposed by Hansen and Singleton (1982) for the estimation of dynamic continuous decision models. We first show that DDC models can be represented as models of continuous choice where the decision variable is a vector of choice probabilities. We then prove that the marginal conditions of optimality and the envelope conditions required to construct Euler equations are also satisfied in DDC models. The GMM estimation of these Euler equations avoids the curse of dimensionality associated to the computation of value functions and the explicit integration over the space of state variables. We present an empirical application and compare estimates using the GMM-Euler equations method with those from maximum likelihood and two-step methods.