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Introduction: Decision making is always based on several factors which may affect the possible outcomes, especially in financial markets. Instead of having many criteria which may be required for decision making, “Multiple Criteria Decision Making” (MCDM) models might be used as a tool to reduce all criteria into a single one.

Purpose: The aim of this study is to measure the financial performance of commercial banks listed on Borsa Istanbul (BIST) by the MCDM.

Method: To this end, data from 15 different financial ratios from 11 commercial banks were used between the periods of 2002 and 2018. Both TOPSIS and gray relational analysis (GRA) models were used, which are commonly used in the literature for detecting the financial performance of listed banks in BIST based on their consolidated financial statements.

Results: According to the TOPSIS method, while the best bank is QNB Finansbank, HALKB, a public bank, was determined as the best bank using the GRA method. There is no significant correlation between financial performance indicators and market returns obtained by either method, with exceptions. There is no generally significant correlation detected between financial ratios and market returns. Accordingly, it is concluded that the bank stock prices in the study are shaped by the influence of external factors and expectations. The study results include information that can be used for different purposes among bank managers, academics and financial investors.

The authors provide new quantitative evidence of the relationship between technologies and organizational design in the context of complex one-off products. The systems that produce complex, one-off products in mature, fragmented industries such as construction lack many of the typical organizational features that researchers have deemed critical to product development success (e.g., team familiarity, frequent communication, and strong leadership). In contrast, the complexity of these products requires a diverse knowledge base that is rarely found within a single firm. The one-off nature of construction’s products further requires improvization and development by a distributed network of highly specialized teams. And because the product is complex, significant innovations in the end product require systemic shifts in the product architecture. Riitta Katila, Raymond E. Levitt and Dana Sheffer use an original, hand-collected dataset of the design and construction of 112 energy-efficient “green” buildings in the United States, combined with in-depth fieldwork, to study these questions. A key conclusion is that the mature US construction industry, with its particularly fragmented supply chain, is not well suited to implementing “systemic innovations” that require coordination across trades or stages of the project. However, project integration across specialists with the highest levels of interdependence (i.e., craft, contract integration) mitigates the knowledge and coordination problems. There are implications for research on how technology shapes organizations (and particularly how organizations shape technology), and on the supply chain configuration strategies of firms in the construction industry as well as building owners who are seeking to build the best buildings possible within their budgets.

International harmonization of accounting standards and the move toward convergence have revived an increasing interest in the influence of culture in accounting and auditing. The growing number of countries adopting IFRS and the increasing acceptance of International Standards on Auditing (ISA) has further raised researchers’ attention. For example, more than 100 countries require or permit the use of IFRS, with more countries, such as Canada, India, and Korea, planning to adopt IFRS by 2011 (Deloitte Touche Tohmatsu, 2007; IASB, 2007a, 2007b). This move toward convergence is driven largely on assumptions and assertions based on enhancing international comparability of accounting and auditing information.

Neuroscience research on human motivation in the workplace is still in its infancy. There is a large industrial and organizational (IO) psychology literature containing numerous theories of motivation, relating to prosocial and productive, and, less so, “darker” antisocial and counter-productive, behaviors. However, the development of a viable over-arching theoretical framework has proved elusive. In this chapter, we argue that basic neuropsychological systems related to approach, avoidance, and their conflict, may provide such a framework, one which we discuss in terms of the Reinforcement Sensitivity Theory (RST) of personality. We argue that workplace behaviors may be understood by reference to the motivational types that are formed from the combination of basic approach, avoidance, and conflict-related personalities. We offer suggestions for future research to explore workplace behaviors in terms of the wider literature on the neuroscience of motivation.

Food system channels are proposed to be major components of the larger food system which influence health and illness.

Food system channels are defined, discussed in relationship to other food system components, considered in terms of historical food system changes, examined in relationship to wellbeing and disease, and proposed to have useful applications.

Food system channels are broad, organized, and integrated pathways through which foods and nutrients pass. Channels are larger in scale and scope than previously described food system structures like chains, stages, sectors, networks, and others. Four major types of contemporary Western food system channels differ in their underlying values and health impacts. (1) Industrialized food channels are based on profit as an economic value, which contributes to a diversity of inexpensive foods and chronic diseases. (2) Emergency food channels are based on altruism as a moral value, and try to overcome gaps in industrialized channels to prevent diseases of poverty. (3) Alternative food channels are based on justice and environmentalism as ethical values, and seek to promote wellness and sustainability. (4) Subsistence food channels are based on self-sufficiency as a traditional value, and seek self-reliance to avoid hunger and illness. Historical socioeconomic development of agricultural and industrial transitions led to shifts in food system channels that shaped dietary, nutritional, epidemiological, and mortality transitions.

Food system channels provide varying amounts of calories and types of nutrients that shape wellbeing and diseases. Sociologists and others may benefit from examining food system channels and considering their role in health and illness.

The strategic management literature emphasizes the concept of business intelligence (BI) as an essential competitive tool. Yet the sustainability of the firms’ competitive advantage provided by BI capability is not well researched. To fill this gap, this study attempts to develop a model for successful BI deployment and empirically examines the association between BI deployment and sustainable competitive advantage. Taking the telecommunications industry in Malaysia as a case example, the research particularly focuses on the influencing perceptions held by telecommunications decision makers and executives on factors that impact successful BI deployment. The research further investigates the relationship between successful BI deployment and sustainable competitive advantage of the telecommunications organizations. Another important aim of this study is to determine the effect of moderating factors such as organization culture, business strategy, and use of BI tools on BI deployment and the sustainability of firm’s competitive advantage.

This research uses combination of resource-based theory and diffusion of innovation (DOI) theory to examine BI success and its relationship with firm’s sustainability. The research adopts the positivist paradigm and a two-phase sequential mixed method consisting of qualitative and quantitative approaches are employed. A tentative research model is developed first based on extensive literature review. The chapter presents a qualitative field study to fine tune the initial research model. Findings from the qualitative method are also used to develop measures and instruments for the next phase of quantitative method. The study includes a survey study with sample of business analysts and decision makers in telecommunications firms and is analyzed by partial least square-based structural equation modeling.

The findings reveal that some internal resources of the organizations such as BI governance and the perceptions of BI’s characteristics influence the successful deployment of BI. Organizations that practice good BI governance with strong moral and financial support from upper management have an opportunity to realize the dream of having successful BI initiatives in place. The scope of BI governance includes providing sufficient support and commitment in BI funding and implementation, laying out proper BI infrastructure and staffing and establishing a corporate-wide policy and procedures regarding BI. The perceptions about the characteristics of BI such as its relative advantage, complexity, compatibility, and observability are also significant in ensuring BI success. The most important results of this study indicated that with BI successfully deployed, executives would use the knowledge provided for their necessary actions in sustaining the organizations’ competitive advantage in terms of economics, social, and environmental issues.

This study contributes significantly to the existing literature that will assist future BI researchers especially in achieving sustainable competitive advantage. In particular, the model will help practitioners to consider the resources that they are likely to consider when deploying BI. Finally, the applications of this study can be extended through further adaptation in other industries and various geographic contexts.

In a computer-based experimental study, we explored intensity of pleasant and unpleasant emotional experiences (affect), following immediate outcomes of risky choices over time under three levels of uncertainty (80%, 50%, 20%). We found that the intensity of pleasant affect initially increased linearly before suddenly reducing after the seventh task, and then resumed the linear upward trend. In contrast, the intensity of unpleasant affect cyclically changed after every five decision tasks, displaying a wave-like pattern. Interestingly, the 50% probability (maximum information entropy) group demonstrated patterns quite different to the other two groups (20%, 80%). For pleasant affect, this group reduced in positive affect significantly more than the other two groups after the seventh decision task. For unpleasant affect, the 50% group displayed an increasing negative affect trend, while the other two groups displayed a reducing negative affect trend. In sum, our findings reveal different temporal patterns of pleasant emotions from correct decisions and unpleasant emotions resulting from wrong decisions. We conclude that, consistent with the self-organization theory, these differences reflect nonlinear changes in the emotional system to cope with the challenge of uncertainty (or entropy).

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.

In a world that glorifies power, the lives of the powerless serve as context for testimonies of salvation that in their pretentiousness more often reinforce the reputation and self-esteem of the powerful hero than transform the lives of the oppressed. Whereas these types of popular human-interest stories may raise awareness of the conditions surrounding the powerless, they do little more than advance the notion that these individuals are without hope and must rely solely on the generosity, resources, and leadership of the powerful populations by which they are exploited. We seek to offer a contrasting perspective in this chapter. That is, we present a framework that challenges messianic notions of leaders of ineffectual populations and presses forth with the idea that powerlessness is a more common condition than feeling powerful and that only the powerless can alter their destiny.

This chapter asks: ‘How often do we as social scientists question the validity of our theories and our findings? How often do we reflexively examine the distortions in the lenses we use to analyse organizations? ‘It proceeds to answer these questions by defining reflexivity and presenting six perspectives on reflexive analysis that build on and extend previous analytical treatments of reflexivity, especially that by Alvesson, Hardy, and Harley (2008). Illustrations of the six are drawn from my own experiences as well as those of other scholars. The intention is to stimulate greater interest in reflexivity and provoke other scholars to look more reflexively at their own work.