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This paper aims to examine how consumers perceive incomplete information in print apparel advertisements in magazines and whether incomplete information influences decisions.

A total of 239 examples of print apparel advertisements in fashion magazines were collected in 2006. Content analysis was utilised to code the types of information in print apparel advertisements prior to the design of the questionnaire in the consumer survey. In the questionnaire, attitudes toward incomplete information in print apparel advertisements, information search, involvement, purchasing intentions, and demographics were included. A consumer survey was administered in Taiwan using stratified sampling. The total number of completed, usable questionnaires returned was 304.

Consumers who thought missing information in print apparel advertising to be important tended to find missing information from other sources like media, word‐of‐mouth, salespersons, and in stores. Information search behaviour positively influenced purchasing intentions. Consumers with higher levels of involvement tended to pay more attention to missing information and were more likely to search information.

Print apparel advertisements are presented not only in magazines, but on outdoor billboards, in catalogues, on the internet, in newspapers, and in buses. The restrictions of readers of fashion magazines as respondents in the study could limit the applicability of research findings of the study to attitudes toward incomplete information in print apparel advertisements of fashion magazine readers.

Print apparel advertisements are not a major source for consumers to obtain comprehensive fashion information. Simplified but clear design of print apparel advertising is acceptable for consumers who are prone to ignore missing information. Those who tend to notice missing information in print apparel advertisements would investigate other sources to obtain information for purchase decisions. Print apparel advertisements showing fashion clothing and brand names only are easy for browsing. The attractiveness of print apparel advertising design seems to be more important than detailed information included in advertisements.

The contribution of the study is to reveal attitudes toward incomplete information in print apparel advertising. The results of the study could be beneficial for apparel advertisers and could be valuable for marketers to realise the types of information consumers prefer while searching though the medium of fashion magazines.

The purpose of this paper is to show that outsourcing can occur as outcome of a separating or pooling perfect Bayesian equilibrium although it is not profitable under complete information. Therefore, asymmetric information can itself be a reason for outsourcing.

The present paper constructs a model of two firms interacting in the product market under asymmetric information where one firm has private information about its technological capability, and it has the option to produce inputs in-house or buy inputs from an input market. However, using outsourced inputs involves a fixed cost at the plant level. The model solves for perfect Bayesian equilibrium.

There are situations when under complete information, outsourcing of the input will not occur, but, under incomplete information, either only the low-cost type or both high and low-cost types will go for outsourcing, and there always exist reasonable beliefs supporting these equilibria. In particular, when the fixed cost is neither too small not too large, a separating equilibrium occurs in which the low-cost type outsources inputs from the input market but the high-cost type produces in-house; hence, outsourcing signals the firm’s type. Outsourcing by only the high-cost type firm will never occur in equilibrium.

That incomplete or asymmetric information can itself be a reason for strategic outsourcing is never identified in the literature. The present paper is an attempt to fill this gap and raise the issue of outsourcing in an incomplete information environment.

The debate over how services should be advertised and communicated has raged on for decades. Much of the early work on services emphasized the use of tangible cues and was primarily issue and/or profession specific. There are no real communication guidelines that encompass all service marketers. This paper looks at how consumers use information in a purchase situation to establish communication guidelines for service providers. Marketers know consumers rarely have full information in a buying situation and have devised communication strategies accordingly. Services in particular offer less information than traditional consumer goods because of services inherent distinguishing characteristics, e.g. intangibility, non‐standardization and concurrent production and consumption. Integrating both conceptual and empirical work this paper uses a framework of incomplete information to examine commonly practiced communication methods of advertising, signaling, personal sources and relationship marketing. Using the two‐dimensional framework advanced in this paper, 16 communication guidelines for service providers are presented.

This paper aims to explore the connectivity between social media use, access to migrant networks, information asymmetry and migration intentions.

The study was conducted using data from individuals living in Nigeria and analysed with a generalized structural equation model, which is rare for this kind of research.

The authors find a dual mediating role of the social media and the migrant networks in facilitating migration, i.e. reducing the threshold cost required to migrate and introducing a bias in terms of information asymmetry. While social media and access to migrant networks directly increase migration intentions, this changes when incomplete information is provided. People who use social media and their migrant networks for information are more likely to have information about destination countries than information on the transit risk.

The study adds valuable insights for designing awareness campaigns aimed at reducing irregular migration.

This study contributes to the understanding of the intersection of migration and digitalization

The purpose of this paper is to offer a “how to” guide for applying Merton’s (1987) valuation adjustment for incomplete information, which depends on market capitalization, idiosyncratic risk and extent of investor ownership.

The paper illustrates Bodnaruk and Ostberg’s (2009) formula for Merton’s adjustment, and presents some example empirical estimates of the adjustment for some US stocks.

The adjustment estimates are material for many example stocks, particularly volatile stocks with a low percentage of shares held by institutional funds. However, the adjustment estimates are modest for many other stocks, including some smaller cap. stocks.

Measuring the model’s inputs requires using some judgment, particularly regarding the investor ownership variable. The paper will hopefully help stimulate useful empirical research on adjustment estimates and on best practices for applying the model.

The paper may encourage more use of the incomplete-information adjustment in practice, which should lead to improved discount rate estimates in valuation analyses.

No other “bridge the gap” coverage of the incomplete-information adjustment is available in textbooks or the applied literature.

This paper aims to exploit the varying level of responses to the carbon disclosure project (CDP) to assess the economic consequences of carbon emission disclosure by disclosure level. Economic theory suggests that increased disclosures by a firm should lower the information asymmetry component of the firm’s cost of capital. Using CDP disclosures by US firms, the authors study the effect of voluntary carbon emission on the information asymmetry risk in capital markets.

The authors conduct cross-sectional analyses to examine whether, from the investor perspective, firms with varying CDP disclosure levels experience differential information asymmetric risk. The authors also conduct a pre- and post-disclosure comparison to examine whether the market responds to first-time carbon emission disclosure with decreases in the relative bid-ask spread.

In the cross-sectional analysis, the authors find that firms that decline to disclose carbon emission information, firms that provide incomplete information and firms that do not respond to the CDP survey have higher information asymmetry than firms that provide complete information and opt to make it available to the public. Using a pre- and post-disclosure comparison, the authors find that the market responds to first-time carbon emission disclosure with decreases in the relative bid-ask spread. Additionally, only firms that participate, provide complete disclosures and opt to make it available to the public enjoy the largest reduction in bid-ask spreads, which is followed by firms that provide incomplete information. Other firms do not experience a reduction in information asymmetry.

This study examines the impact of CDP disclosures on information asymmetry using a US sample. The results of the study may not be generalizable to other countries that have different institutional arrangements and settings.

The study has important social and policy implications. The findings on the role of carbon emission disclosures in reducing information asymmetry in the capital markets suggest the need for policymakers to promote greater carbon emission disclosures in the USA and other countries where such disclosures have been traditionally less emphasized. As to stakeholders, bringing corporate carbon emission disclosure in line with recommended guidelines will require them to exercise more direct stakeholder pressure to encourage firms to fully participate in the CDP project. This is particularly critical in settings of regulatory inaction and weak enforcement with respect to environmental policies and disclosure such as the USA.

The results span the current gap between two broad perspectives on corporate social responsibilities. The traditional shareholder perspective argues that companies only participate in socially responsible activities which increase shareholder value, while an alternate perspective argues that companies also undertake social responsibilities to benefit society even at the cost of shareholders (Moser and Martin, 2012). The study demonstrates that the two perspectives are not always at odds, carbon emission disclosure not only provides important information on the corporate social responsibility of the firm but also contributes to enriching the information environment leading to reduced information asymmetry in the equity markets for US firms. Thus, from both a stakeholder and capital market perspective, firms have incentives to provide carbon emission disclosures voluntarily. More direct stakeholder pressure may be helpful to encourage more firms to provide complete carbon emission information and opt to make it available to the public.

Few studies investigate the impact of CDP disclosure on the information environment of public companies. The lack of research on this key connection between new disclosures on carbon emissions and information asymmetry in the capital markets is the primary motivation for the paper. The study also provides important insights on disclosure level; just participating in the CDP survey is not enough, the degree of participation is also important. The results of the study suggest that the varying level of disclosure matters, the greatest benefits in terms of reduction of information asymmetry accrue to firms that provide complete information and opt to make it available to the public.

The purpose of this paper is to propose a multi‐attribute decision‐making method based on the concept of extended dominance relation and variable precision rough sets.

First, the definitions of extended dominance relation and variable precision rough sets are introduced in detail. Second, two types of extended dominance rules are obtained from the pairwise comparison table. Third, a scoring function is defined and sorted to score all the objects. Finally, a case about the emergency decision making after an earthquake is discussed to demonstrate the feasibility and efficiency of the method.

It is found that the new method can deal with decision‐making problems with incomplete information. Numerical examples show that the method has good application prospects in public emergency decision making, including an earthquake emergency.

The method shown in the paper can be used for solving decision‐making problems with incomplete information.

The paper develops a novel multi‐attribute decision analysis method dealing with incomplete information based on rough sets theory.

The purpose of this paper is to show which models, uncertain or certain, simple or complicated, are more suitable when they are faced with incomplete information and inaccurate data.

The characteristics of fuzzy mathematics, grey system theory, rough set theory and the basic characteristics of incomplete information and inaccurate data in uncertain systems are analysed.

The similarities and differences among fuzzy mathematics, grey system theory, rough set theory and probability statistics are compared. The principle of simplicity of scientific theories, methods, and models are discussed.

It is suggested that the tendency to concentrate on a complicated model isn't always necessary when faced with the condition of incomplete information and inaccurate data.

The paper shows that a more satisfied result can be obtained with an uncertain model than with a meticulous model on a certain situation.

The purpose of this paper is to introduce the elementary concepts and fundamental principles of grey systems and the main components of grey systems theory. Also to discuss the astonishing progress that grey systems theory has made in the world of learning and its wide‐ranging applications in the entire spectrum of science.

The characteristics of unascertained systems including incomplete information and inaccuracies in data are analysed and four uncertain theories: probability statistics, fuzzy mathematics, grey system and rough set theory are compared. The scientific principle of simplicity and how precise models suffer from inaccuracies are also shown.

The four uncertain theories, probability statistics, fuzzy mathematics, grey system and rough set theory are examined with different research objects, different basic sets, different methods and procedures, different data requirements, different emphasis, different objectives and different characteristics.

The scientific principle of simplicity and how precise models suffer from inaccuracies are shown. So, precise models are not necessarily an effective means to deal with complex matters, especially in the case that the available information is incomplete and the collected data inaccurate.

The elementary concepts and fundamental principles of grey systems and the main components of grey systems theory are introduced briefly. The reader is given a general picture of grey systems theory as a new method for studying problems where partial information is known, partial information is unknown; especially for uncertain systems with few data points and poor information.

The purpose in this article is to examine some implications which arise from assuming agents faced a mixed information structure for some standard tests of the rational expectations hypothesis.