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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.

This paper investigates the income dynamics of Italian primary sector, during and after the international economic crisis. It focuses on three research questions: what has been the evolution of the main profitability ratios of agricultural enterprises in recent years? After the crisis, have the surviving farms increased their profitability? Has the profitability been different also in relation to the geographic location?

Income dynamics of a sample of companies have been analyzed, obtaining the 10-year evolution of the average value of three income indices (return on equity [ROE], return on assets [ROA] and return on sales [ROS]). Statistical elaborations and the analysis of variance (ANOVA) method have been used.

The years of the international economic crisis are often characterized by higher incomes than the following ones. The descending trend involves all three national macroareas of Italy, although characterized by considerable socioeconomic differences.

The study considers only the society that survived the crisis, so, presumably, the strongest. Moreover, other ratios should be considered in order to have a more complete view.

Public policymakers could use this study for a better intervention in support of agricultural and agro-industrial activities.

The careful economic and financial analysis of the sector favors the relaunching strategies of the Italian primary sector in which many employees work.

The research contributes to the literature by providing a quantitative analysis of the dynamics of the sector, through the comparative information that may be derived from financial statements.

This study illustrates the economic and financial dynamics of the sector, analysing the evolution of the main ratios of profitability and financial structure of 1,559 Italian real estate companies divided into the three macro-regions: North, Centre and South, in the period 2011–2020. In this way, it is also possible to verify the responsiveness to the 2020 pandemic crisis.

The analysis uses descriptive statistics tools and the ANOVA method of analysis of variance, supplemented by the Tukey–Kramer test, to identify significant differences between the three Italian macro-regions.

The study shows the increase in profitability after the 2008 crisis, despite its reverberation in the years 2012–2013. The financial structure of companies improved almost everywhere. The pandemic had modest effects on performance.

In the future, other indices should be considered to gain a more comprehensive view. This is a quantitative study based on financial statements data that neglects other important economic and social factors.

Public policies could use this study for better interventions to support the sector. In addition, internal management can compare their company's performance with the industry average to identify possible improvements.

The research analyses an economic field that employs a large number of people, especially when considering the construction and real estate services covered by this analysis.

The study contributes to the literature by providing a quantitative analysis of industry dynamics, with comparative information that can be deduced from financial statements over the years.