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In this chapter we study the peer comparable approach used for the valuation of companies that went public on the Italian Nuovo Mercato. In Italy, IPO prospectuses often report the valuation methods used by investment banks. This allows us to analyze the accuracy of “real-world” valuation estimates. We show that underwriters rely on price-to-book and price-earnings multiples. The valuation estimates generated by these multiples are closest to offer prices. Conversely, when using enterprise value ratios comparable firms’ multiples are typically higher than those of the firms going public. We argue that underwriters have the possibility to select comparables that make their valuations look conservative.

Land bank distribution in India is a complex subject and with the family size reduction, the average land holding is going down. Maintenance of the land records in physical format is very difficult. There are thousands of court disputes for different land parcels and managing the same is becoming a complex task. The aim of the chapter is to design a conceptual framework with electronic landbank records in dematerialized form, so that they can be easily maintained and traded. Associated benefits of implementing such system are also discussed. Authors have used secondary data published in previous research work in the area of Geographical Information System (GIS) and business analytics to analyze the prospects of land bank dematerialization and its possible applications. The chapter focuses on the need of regulatory support and associated IT infrastructure to put the plan in action. If implemented, this change can help India to transform its land management process and will also enable to explore commercial utilization of agricultural land and urban land plots for planned development.

The increasing availability of eXtensible Business Reporting Language (XBRL) financial statements motivates additional investigation of whether XBRL’s search-facilitating technology (SFT) and enhanced viewing capabilities facilitate information search and improve financial analysis decision quality and efficiency. This experiment investigates how using XBRL technology to view financial statements influences novice investors’ decision quality by affecting decision processes such as search strategy and effort, as well as decision efficiency (accuracy/effort) in a financial statement analysis task. In the experiment, randomly assigned student participants (n = 102) invested in companies using either static PDF-formatted or XBRL-enabled financial statements. No differences in decision quality (i.e., accuracy) due to technology use were observed. However, participants in the XBRL condition examined less information, used more directed search processes, and evidenced greater efficiency than did participants assigned to the PDF condition. Hence, the results suggest that XBRL SFT affects the use of differing decision processes relative to PDF technology.

This paper proposes and tests a model to explain the outcomes of three different information presentation formats. Based on cognitive fit theory, information visualization formats that best fit task characteristics are expected to lead to improved decision-making outcomes. We apply the Judgment and Decision-Making framework (Bonner, 2008) to investigate how certain factors can impact decision quality.

This study tests whether certain production variance presentation formats (percentages, dollar amounts, and schematic faces), task complexity, understanding of the presentation format, motivation, and effort increase the accuracy of a supervisor’s bonus calculation. A total of 281 students and professionals participated in this experiment. Their responses were examined using regression analysis.

Our results indicate that individuals mostly prefer the percentages presentation format and that the use of the percentages presentation format, a lower level of task complexity, and a better understanding of the variance presentation format lead to more accurate calculations in the experimental task.

Our study provides a call for further research on factors that influence the choice of presentation format as a potentially fruitful area for management accounting researchers.

We exhort practicing management accountants to exert direct influence on employees’ decision making through the use of variance presentation formats that fit their tasks and promote understanding.

Our experiment introduced two major innovations: it uses an interactive data visualization approach allowing subjects to select their preferred presentation format; and it focuses on production variances, a topic that has received less attention in the academic managerial accounting literature, but is still very relevant to practitioners.

In the last few decades, there has been growing interest in forecasting with computer intelligence, and both fuzzy time series (FTS) and artificial neural networks (ANNs) have gained particular popularity, among others. Rather than the conventional methods (e.g., econometrics), FTS and ANN are usually thought to be immune to fundamental concepts such as stationarity, theoretical causality, post-sample control, among others. On the other hand, a number of studies significantly indicated that these fundamental controls are required in terms of the theory of forecasting, and even application of such essential procedures substantially improves the forecasting accuracy. The aim of this paper is to fill the existing gap on modeling and forecasting in the FTS and ANN methods and figure out the fundamental concepts in a comprehensive work through merits and common failures in the literature. In addition to these merits, this paper may also be a guideline for eliminating unethical empirical settings in the forecasting studies.

Prior studies have shown that terminology support can improve health information retrieval but have not taken into account the characteristics of the user performing the search. In this chapter, the impact of translating queries’ terms between lay and medico-scientific terminology, in users with different levels of health literacy and topic familiarity, is evaluated. Findings demonstrate that medico-scientific queries demand more from the users and are mostly aimed at health professionals. In addition, these queries retrieve documents that are less readable and less well understood by users. Despite this, medico-scientific queries are associated with higher precision in the top-10 retrieved documents results and tend slightly to generate knowledge with less incorrect contents, the researchers concluded that search engines should provide query suggestions with medico-scientific terminology, whenever the user is able to digest it, that is, in users above the lowest levels of health literacy and topic familiarity. On the other hand, retrieval systems should provide lay alternative queries in users with inadequate health literacy or in those unfamiliar with a topic. In fact, the quantity of incorrect contents in the knowledge that emerges from a medico-scientific session tends to decrease with topic familiarity and health literacy. In terms of topic familiarity, the opposite happens with Graded Average Precision. Moreover, users most familiar with a topic tend to have higher motivational relevance with medico-scientific queries than with lay queries. This work is the first to consider user context features while studying the impact of a query processing technique in several aspects of the retrieval process, including the medical accuracy of the acquired knowledge.