What's in a logo? The impact of complex visual cues in equity crowdfunding

Visual cues are pervasive on crowdfunding platforms. However, whether and how low validity visual cues can impact the behavior of backers remains largely unknown. In this article, we propose a disfluency-based heuristic framework for understanding the influence of low validity visual cues on equity crowdfunding platforms. Drawing on processing fluency theory and visual heuristics, we propose that backers often automatically process visual cues, and that the subjective experience of ease/difficulty with which backers perceptually process low validity visual cues serves as a heuristic and informs their perceptions of early-stage entrepreneurial ventures. We test our propositions focusing on logos (low validity visual cues that are particularly salient and ubiquitous on equity crowdfunding platforms) and logo complexity (a fundamental characteristic of logo design and established antecedent of processing disfluency). We contend that logo complexity can be interpreted by backers as a signal of venture innovativeness because more (vs. less) complex logos are more difficult to process, and thus, feel less familiar and more unique, original, and novel to backers. Since backers often value innovativeness, we further contend that logo complexity can positively impact backers' funding decisions. We find support for our framework and propositions using a multimethod approach comprising three studies: one survey, one field study, and one experiment. Theoretical contributions and managerial implications are also discussed.     

What drives global B2B e-commerce usage: an analysis of the effect of the complexity of trading system and competition pressure

The purpose of this paper is to examine the conditions in which B2B e-commerce is most likely to diffuse widely at the country level. This paper examines the role of trading system complexity and pressure of competition on B2B EC diffusion by controlling Gross domestic product (GDP) per capita and Information and Communication Technology (ICT) infrastructure. Our sample comprises a pool of country-year dataset from 143 countries over a three-year period (2014–2016). The data were collected from Network Readiness Index Report and Global Competitiveness Report. The findings provide evidence that greater the complexity of trading relationships with the global economy and high level of pressure from the competition are the main forces for B2B use across countries. Consequently, the authors suggest that having a strong trade relationship with developed countries with matured B2B e-commerce practice is helpful in sustaining B2B e-commerce use across countries.     

New development: The application of incomplete contract theory to documenting Social Impact Bonds

ABSTRACT

Nobel laureate Oliver Hart’s work in developing a theory of incomplete contracting is relevant to explaining the evolution of the pay for success contracts that undergird Social Impact Bonds (SIBs). By its very nature, a pay for success contract that supports a SIB is likely to be functionally incomplete in that it is unable to describe and differentiate in the initial contract all relevant future states of the world in which the contract is to operate. Navigating this incomplete world can be particularly challenging when it comes to government contracting for quality outcomes in social services. Accordingly, Hart’s incomplete contracting framework can help us to think more clearly about how to document a pay for success contract that best supports a SIB transaction.     

Environmental degradation,energy consumption and sustainable development: Accounting for the role of economic complexities with evidence from World Bank income clusters

The anthropogenic consequences of renewable and non-renewable energy consumption, economic growth, and air transport have been assessed enormously in the literature. However, given the complexities in many economies of the world today, it is important to reassess the ecological concerns of these factors in light of the Environmental Kuznets Curve framework. Therefore, this current study investigates the global assessment using data from World Bank Development database from 1995 to 2016. Evidence from the method employed, sys-GMM, revealed that the economic complexities index increases the carbon emission in low-income groups while it significantly decreases the carbon emission for upper-middle and high-income groups. For the combined group, the EKC hypothesis holds, and ECI significantly hampers carbon emissions. For the other variables, it is worthy of note that (1) economic growth contributes to the high carbon contents across the income group especially for low-income, upper-middle-income and high-income group; (2) the effects of air transport on carbon emission is positive for lower-middle-income and high-income group and negative for the upper-middle-income group; (3) the use of coal rents and energy use leads to high release of carbon contents across all the income groups; and (4) a significant increase in the utilization of energy leads to increase in carbon contents except for lower-income group, it leads to a decrease. From this empirical assessment, vital energy policy directions are suggested.     

Contractual corporate governance

Companies have the choice to deviate from their national corporate governance standards by opting into another system. They can do so via contractual devices – such as cross-border mergers and acquisitions, (re)incorporations, and cross-listings – which enable them to choose their preferred level of investor protection and regulation. This paper reviews these three main contractual governance devices, their effect on value, and whether their adoption by firms induces a race to the bottom or a race to the top. Indeed, firms may opt for less shareholder-orientation or investor protection (shareholder-expropriation hypothesis) rather than for more stringent rules that require firms to focus on shareholder value (bonding hypothesis).     

Statistical Inference,Learning and Models in Big Data

The need for new methods to deal with big data is a common theme in most scientific fields, although its definition tends to vary with the context. Statistical ideas are an essential part of this, and as a partial response, a thematic program on statistical inference, learning and models in big data was held in 2015 in Canada, under the general direction of the Canadian Statistical Sciences Institute, with major funding from, and most activities located at, the Fields Institute for Research in Mathematical Sciences. This paper gives an overview of the topics covered, describing challenges and strategies that seem common to many different areas of application and including some examples of applications to make these challenges and strategies more concrete.     

EMERGENT COMPLEXITY IN AGENT‐BASED COMPUTATIONAL ECONOMICS

Abstract In this paper, we shall review two kinds of emergent complexity in agent‐based computational economics (ACE). The first kind is based on the complex systems initiated in the 1980s or even earlier by mathematicians and physicists, whereas the second kind is based on the idea of complex adaptive systems composed of autonomous agents, for which many representative works have been collected in Rosser. For the latter, we shall go further to examine the two elements which have just recently been incorporated in agent‐based economic modelling, namely, intelligence and modularity. This augmentation leads to the development of neurocognitive software agents, which can guide the generation and direction of future ACE studies with a multistage ‘brain/behaviour‐to‐emergency‐to‐brain/behaviour’ approach.     

The Emergence of Consolidated Service Centers in Health Care

Hospital supply chains can be conceptualized as complex systems with a large number of players and a high degree of interrelatedness among them, creating an environment that is difficult to optimize and manage. In recent years, a consolidated service center (CSC) strategy (sometimes also referred to as “self‐distribution” strategy), has emerged in some healthcare systems, showing a strong potential for reducing the complexity in a hospital's supply chain to achieve high levels of performance and innovation. We examine three CSCs using a qualitative case method to understand the unique characteristics of this supply chain strategy, and how CSCs move hospital supply chains toward a less complex state. We find that CSCs demonstrate characteristics that distinguish them from other supply chain strategies. These characteristics enable the CSC to orchestrate supply base rationalization and disintermediation initiatives in the hospital's supply chain to effectively reduce the number of components and interrelatedness in this complex system.