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It is possible to see effective use of Artificial Intelligence-based systems in many fields because it easily outperforms traditional solutions or provides solutions for the problems not previously solved. Prediction applications are a widely used mechanism in research because they allow for forecasting of future states. Logical inference mechanisms in the field of Artificial Intelligence allow for faster and more accurate and powerful computation. Machine Learning, which is a sub-field of Artificial Intelligence, has been used as a tool for creating effective solutions for prediction problems.

In this chapter the authors will focus on employing Machine Learning techniques for predicting data for future states of economic using techniques which include Artificial Neural Networks, Adaptive Neuro-Fuzzy Inference System, Dynamic Boltzmann Machine, Support Vector Machine, Hidden Markov Model, Bayesian Learning on Gaussian process model, Autoregressive Integrated Moving Average, Autoregressive Model (Poggi, Muselli, Notton, Cristofari, & Louche, 2003), and K-Nearest Neighbor Algorithm. Findings revealed positive results in terms of predicting economic data.

Drawing on insights from a yearlong ethnography and in-depth survey of the members of a Buddhist monastery located in the heart of modern Europe, we examine how members of the organization come to be more or less involved in the organization and in its core institutional logic. Here we present an exploratory analysis of how individuals’ beliefs about Buddhism and its relationship to everyday life are deeply intertwined with and articulated into different regimes of organizational activities, rituals, and religious practices. Borrowing from institutional logics theory, we use methods for illustrating the relational structure that articulates dualities linking beliefs and practices together. We show that dually ordered assemblages can reveal different types of logics embraced by different members of an organization. Our principal contention is that the greater the structural alignment between an individual’s belief structure, their repertoire of practices, and the institutional logic of the organization, the more well integrated that individual will likely be within the organization, the higher the probability of transformational changes of personal identity, as well as the greater probability of overall success in organizational membership recruitment and retention.

Despite the existence of a variety of approaches to the understanding of behavioral and managerial ethics in organizations and business relationships generally, knowledge of organizing systems for fidelity remains in its infancy. We use halakha, or Jewish law, as a model, together with the literature in sociology, economic anthropology, and economics on what it termed “middleman minorities,” and on what we have termed the Landa Problem, the problem of identifying a trustworthy economic exchange partner, to explore this issue.

The article contrasts the differing explanations for trustworthy behavior in these literatures, focusing on the widely referenced work of Avner Greif on the Jewish Maghribi merchants of the eleventh century. We challenge Greif’s argument that cheating among the Magribi was managed chiefly via a rational, self-interested reputational sanctioning system in the closed group of traders. Greif largely ignores a more compelling if potentially complementary argument, which we believe also finds support among the documentary evidence of the Cairo Geniza as reported by Goitein: that the behavior of the Maghribi reflected their deep beliefs and commitment to Jewish law, halakha.

Applying insights from this analysis, we present an explicit theory of heroic marginality, the production of extreme precautionary behaviors to ensure service to the principal.

Generalizing from the case of halakha, the article proposes the construct of a deep code, identifying five defining characteristics of such a code, and suggests that deep codes may act as facilitators of compliance. We also offer speculation on design features employing deep codes that may increase the likelihood of production of behaviors consistent with terminal values of the community.

In today's knowledge-based economy, the ability to produce highly novel and practical ideas is critical to an organization's survival. This paper draws upon social perspectives of creativity (Perry-Smith & Shalley, 2003) and the vital role of recombinant information in creative development (Barron & Harrington, 1981; Hargadon, 2003) to explore information exchange probabilities; exchanges among group members who are deep-level similar fosters incremental creative potential while information exchanges among group members who are deep-level dissimilar fosters radical creative potential. The dynamics of attraction suggest group members are most likely to interact with people who are least likely to facilitate radical creativity. Using a computer simulation we examine how proximity may be used to facilitate information exchanges among deep-level diverse group members to increase the potential for radical creativity. Results suggest the use of proximity to create strong ties among deep-level dissimilar group members may facilitate radical creativity in groups.

University libraries have traditionally been the primary caretaker of scholarly resources. However, as electronic modes of information delivery replace print materials, expectations of academic libraries have evolved rapidly. In this environment, academic libraries need to be adaptable organizations. Librarianship, though, is deeply rooted in strong values and beliefs which inherently limit receptivity to change and innovation, but these constraints are not absolute. Social network research indicates that professional advice networks play a significant role in how one thinks about and performs work and that individual perspectives are broadened when diverse input is received. Based on social network analysis methods, this study explored the relationship between individual receptivity to innovation and the composition of a person's professional advice network through a purposive sample of academic librarians in Illinois. The group completed a survey that explored two dimensions: (1) the nature of relationships within their professional advice network and (2) the individual's personal receptivity to innovation. Analysis of the nature of relationships within the professional advice networks was based on a combination of quantitative and qualitative techniques, in contrast to the analysis of the respondents’ receptivity to innovation which was based on quantitative measures. Based on the information from the 440 respondents, the results of this research indicate that there is a relationship between the size of the professional advice networks and individual's receptivity to innovation, but additional aspects of the professional advice network may play a role in an individual's overall receptivity to innovation.

We introduce a multi-level model of the dependence of interfirm network topologies on the distribution and commonality of information in a network and the information strategies pursued by its member firms. Network topology, information properties of the network, and firm-level action within the network form dynamic, recursive, cross-level relationships – information properties in the network determine firm-level action, which in turn impacts the network topology and information properties. We derive predictions about the kinds of information strategies that firms are likely to adopt and succeed with in different information regimes, and about the kinds and short- and long-run dynamics of network topologies expected under different information regimes. Our model sheds new light on network topologies as a dependent variable that can be explained by network-level information regimes and firm-level information strategies.

The study this chapter reports focuses on how network theory contributes to the understanding of the internationalization process of SMEs and measures the effect of network capability on performance in international trade and has three research objectives.

The first objective of the study relates to providing new insights into the international market development activities through the application of a network perspective. The chapter reviews the international business literature to ascertain the development of thought, the research gaps, and the shortcomings. This review shows that the network perspective is a useful and popular theoretical domain that researchers can use to understand international activities, particularly of small, high technology, resource-constrained firms.

The second research objective is to gain a deeper understanding of network capability. This chapter presents a model for the impact of network capability on international performance by building on the emerging literature on the dynamic capabilities view of the firm. The model conceptualizes network capability in terms of network characteristics, network operation, and network resources. Network characteristics comprise strong and weak ties (operationalized as foreign-market entry modes), relational capability, and the level of trust between partners. Network operation focuses on network initiation, network coordination, and network learning capabilities. Network resources comprise network human-capital resources, synergy-sensitive resources (resource combinations within the network), and information sharing within the network.

The third research objective is to determine the impact of networking capability on the international performance of SMEs. The study analyzes 11 hypotheses through structural equations modeling using LISREL. The hypotheses relate to strong and weak ties, the relative strength of strong ties over weak ties, and each of the eight remaining constructs of networking capability in the study. The research conducts a cross-sectional study by using a sample of SMEs drawn from the telecommunications industry in Ireland.

The study supports the hypothesis that strong ties are more influential on international performance than weak ties. Similarly, network coordination and human-capital resources have a positive and significant association with international performance. Strong ties, weak ties, trust, network initiation, synergy-sensitive resources, relational capability, network learning, and information sharing do not have a significant association with international performance. The results of this study are strong (R2=0.63 for performance as the outcome) and provide a number of interesting insights into the relations between collaboration or networking capability and performance.

This study provides managers and policy makers with an improved understanding of the contingent effects of networks to highlight situations where networks might have limited, zero, or even negative effects on business outcomes. The study cautions against the tendency to interpret networks as universally beneficial to business development and performance outcomes.