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Artificial neural networks are highly flexible and efficient tools in the approximation of time series patterns. In recent years, more than 5,000 studies oriented to the use of neural networks in time series forecasting have been evidenced in the extant literature. However, the methodology used for its specification and construction still involves a lot of trial and error or is inherited from econometric and statistical procedures that do not fit perfectly to the characteristics of the time series. This is especially true when they present non-linear behavior; moreover, it is not designed for working with neural networks. The objective of this chapter is to present a five-step guide for the specification, design, and validation of a neural network model for forecasting time series.

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Approximately 90% of companies are Micro, Small, and Medium Enterprises (MSMEs) and Small & Medium Enterprises (SMEs). Their importance in the economy lies in the fact that they account for almost 60% of the jobs in the world, number which could be greater in developing countries. All these companies have an environmental impact that is almost imperceptible when observed individually, but if observed and analyzed as a whole, this impact is actually relevant. It is therefore important for these companies to include the concept of sustainability within their processes, which is difficult given the informal way they have managed their activities and processes. On the other hand, there are two paradigms that rule the concept of sustainability, weak sustainability and strong sustainability. As it will be presented in this chapter, both concepts are opposed and companies are normally oriented towards weak sustainability, because they are more interested in economic growth than in caring for the environment.

Electronic word of mouth (eWOM) has an effect on trust prior to purchase of similar branding for both highly branded and off-branded products and services. This chapter shows, through a literature review, the impact of eWOM on building trust and then on sales of search and experience goods. Major findings are presented. eWOM has a stronger impact on the sales of experience goods than on search goods. When considering a purchase online, consumers have more resources about the product or service than those that the retailer or manufacturer provides. These newly available resources are consumer-generated; hence, consumers considering a buy find them more trustworthy. Consumers also value differently whether the consumer-generated content is positive or negative about the product or service they are considering buying. The final part of the chapter discusses the different implications for marketing practitioners.