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People often face constraints such as a lack of time or information in taking decisions, which leads them to use heuristics. In these situations, fast and frugal rules may be useful for making adaptive decisions with fewer resources, even if it leads to suboptimal choices. When applied to financial markets, the recognition heuristic predicts that investors acquire the stocks that they are aware of, thereby inflating the price of the most recognized stocks. This paper aims to study the profitability against the market of the most recognized stocks in Europe.

In this paper, the authors perform a survey and use Google Trends to study the profitability against the market of the most recognized stocks in Europe.

The authors conclude that a recognition heuristic portfolio yields poorer returns than a market portfolio. In contrast, from the data collected on Google Trends, weak evidence was found that strong increases in companies monthly search volumes may lead to abnormal returns in the following month.

The applied investment strategy does not account for transaction costs, which may jeopardize its profitability given the fact that it is necessary to revise the portfolio on a monthly basis. Despite the results obtained, they are useful to understanding the performance of recognition heuristic strategies over a comprehensive time horizon, and it would be interesting to depict its viability during different market conditions. This analysis could provide additional information about a preferable scenario for employing our strategies and, ultimately, enhance the profitability of recognition heuristic strategies.

Through the exhaustive analysis performed here on the recognition heuristic in the European stock market, it is possible to conclude that no evidence was found for the viability of exploring this type of strategy. In fact, the investors would always gain better returns when adopting a passive investment strategy. Therefore, it would be wise to assume that the European market presents at least a degree of efficiency where no investment would yield abnormal returns following the recognition heuristic.

The main objective of this paper is to study the performance of the recognition heuristic in the financial markets and to contribute to the knowledge in this field. Although many authors have already studied this heuristic when applied to financial markets, there is a lack of consensus in the literature.

The aim of this paper is to systematically review the literature published in recognized journals focused on recognition-based heuristics and their effect on investment management activities and to ascertain some substantial gaps related to them.

For doing research synthesis, systematic literature review approach was applied considering research studies published within the time period, i.e. 1980–2020. This study attempted to accomplish a critical review of 59 studies out of 118 studies identified, which were published in reputable journals to synthesize the existing literature in the behavioural finance domain-related explicitly to recognition-based heuristics and their effect on investment management activities.

The survey and analysis suggest investors consistently rely on the recognition-based heuristic-driven biases when trading stocks, resulting in irrational decisions, and an investment strategy constructed by implementing the recognition-based heuristics, would not result in better returns to investors on a consistent basis. Institutional investors are less likely to be affected by these name-based behavioural biases in comparison to individual investors. However, under the context of ecological rationality, recognition-based heuristics work better and sometimes dominate the classical methods. The research scholars from the behavioural finance community have highlighted that recognition-based heuristics and their impact on investment management activities are high profile areas, needed to be explored further in the field of behavioural finance. The study of recognition-based heuristic-driven biases has been found to be insufficient in the context of emerging economies like Pakistan.

The skilful understanding and knowledge of the recognition-based heuristic-driven biases will help the investors, financial institutions and policy-makers to overcome the adverse effect of these behavioural biases in the stock market. This article provides a detailed explanation of recognition-based heuristic-driven biases and their influence on investment management activities which could be very useful for finance practitioners’ such as investor who plays at the stock exchange, a portfolio manager, a financial strategist/advisor in an investment firm, a financial planner, an investment banker, a trader/ broker at the stock exchange or a financial analyst. But most importantly, the term also includes all those persons who manage corporate entities and are responsible for making its financial management strategies.

Currently, no recent study exists, which reviews and evaluates the empirical research on recognition-based heuristic-driven biases displayed by investors. The current study is original in discussing the role of recognition-based heuristic-driven biases in investment management activities by means of research synthesis. This paper is useful to researchers, academicians, and those working in the area of behavioural finance in understanding the role that recognition-based heuristics plays in investment management activities.

This study aims to use a qualitative approach to explore and clarify the mechanism by which heuristic-driven biases influence the decisions and performance of individual investors actively trading on the Pakistan Stock Exchange (PSX). It also aims to identify how to overcome the negative effect of heuristic-driven biases, so that finance practitioners can avoid the expensive errors which they cause.

This study adopts an interpretative approach. Qualitative data was collected in semistructured interviews, in which the target population was asked open-ended questions. The sample consists of five brokers and/or investment strategists/advisors who maintain investors’ accounts or provide investment advice to investors on the PSX, who were selected on a convenient basis. The researchers analyzed the interview data thematically.

The results confirm that investors often use heuristics, causing several heuristic-driven biases when trading on the stock market, specifically, reliance on recognition-based heuristics, namely, alphabetical ordering of firm names, name memorability and name fluency, as well as cognitive heuristics, such as herding behavior, disposition effect, anchoring and adjustment, repetitiveness, overconfidence and availability biases. These lead investors to make suboptimal decisions relating to their investment management activities. Due to these heuristic-driven biases, investors trade excessively in the stock market, and their investment performance is adversely affected.

This study provides a practical framework to explore and clarify the mechanism by which heuristic-driven biases influence investment management activities. To the best of authors’ knowledge, the current study is the first to focus on links between heuristic-driven biases, investment decisions and performance using a qualitative approach. Furthermore, with the help of a qualitative approach, the investigators also highlight some factors causing an increased use of heuristic variables by investors and discuss practical approaches to overcoming the negative effects of heuristics factors, so that finance practitioners can avoid repeating the expensive errors which they cause, which also differentiates this study from others.

Are there smart ways to find heuristics? What are the common principles behind heuristics? We propose an integrative definition of heuristics, based on insights that apply to all heuristics, and put forward meta-heuristics for discovering heuristics.

We employ Herbert Simon’s metaphor that human behavior is shaped by the scissors of the mind and its environment. We present heuristics from different domains and multiple sources, including scholarly literature, practitioner-reports and ancient texts.

Heuristics are simple, actionable principles for behavior that can take different forms, including that of computational algorithms and qualitative rules-of-thumb, cast into proverbs or folk-wisdom. We introduce heuristics for tasks ranging from management to writing and warfare. We report 13 meta-heuristics for discovering new heuristics and identify four principles behind them and all other heuristics: Those principles concern the (1) plurality, (2) correspondence, (3) connectedness of heuristics and environments and (4) the interdisciplinary nature of the scissors’ blades with respect to research fields and methodology.

We take a fresh look at Simon’s scissors-metaphor and employ it to derive an integrative perspective that includes a study of meta-heuristics.

In order to better understand how heuristics are used in practice, the authors explore what type of heuristics is used in the managerial domain of financial advisors to small and medium-sized enterprises (SMEs) and what influences the shaping of these heuristics. In doing so, the authors detect possible fast-and-frugal heuristics in day-to-day decision-making of independent financial advisers who help owners of SMEs to acquire capital (e.g. loans, factoring, leasing and equity).

The authors inductively assessed the work of financial advisers of SMEs. Based on group discussions, the authors drew up a semi-structured interview-protocol with descriptive questions about how financial advisers come to a deal for their clients. The interviews of 19 professionals were analysed by relating them to the theory of fast-and-frugal heuristics.

Within their decision-making, advisers estimate the likelihood of acceptance by a few financial providers they know well in their personal network with a strong bias towards traditional banking products, although there are a large number of alternatives on the Dutch market. “Less is more” seems to be a relevant principle when defined as satisficing. Heuristics help advisers to deal with behavioural and economic limitations. Also, the authors have found that client interaction, previous working experience and the company the adviser is working for influences the shaping of the simple rules the adviser is using.

The study shows how difficult it is to understand the ecological rationality of a certain group of professionals and to understand the “less is more” principle. Financial advisers to SMEs use cognitive shortcuts and simple rules to advise SME-owners, based on previous experiences, but it is difficult to determine whether that leads to the same or even better solutions for them and their clients than using probability theory and financial optimisation models. Within heuristics, satisficing seems to be a dominant mechanism. Here, heuristics help advisers in recognising possibilities by searching for similarities between a current financing case and previous experiences. The data suggests that if “less is more” is defined as satisficing for one or more stakeholders involved, the principle dominates the decision making of financial advisers of SME's.

The authors suggest the relevance of a behavioural approach to finance by assessing the day-to-day decisions of financial advisers of SMEs. Also, the authors suggest that financial advisers are guided by previous experiences, and they do not fully assess a wide range of options in their work but need shortcuts to fulfil the needs of their clients.

The study comes close to day-to-day decision-making in finance by assessing how professionals make decisions. The authors try to understand types of heuristics in relation with “ecological rationality” and the less is more principle. The authors assess financial advisers of SME-companies, a group that has gotten little research attention until now. The influence of client interaction and of the company the adviser is working for is remarkable in the shaping of the advisers' simple rules.

Given the complexity of green public procurement, decisions are likely to be driven by bounded rationality. However, we know little about what determines supplier selection criteria in any given situation. This study explores buyer behavior when considering environmental criteria. We first conducted interviews and identified 12 operational procedures used by buyers. We then developed a survey to explore the use of these procedures. Our quantitative analysis suggests that public buyers are motivated by their belief that they can make a difference. This is independent of buyers' experience or gender. However, their occupational position and the nature of a procurement seem to influence how buyers seek information about environmental criteria and which information source(s) they use. The data suggest that four specific decision-making heuristics are associated with the selected operational procedures.

This study aims to explore and clarify the mechanism by which recognition-based heuristic biases influence the investment decision-making and performance of individual investors, with the mediating role of fundamental and technical anomalies.

The deductive approach was used, as the research is based on behavioral finance's theoretical framework. A questionnaire and cross-sectional design were employed for data collection from the sample of 323 individual investors trading on the Pakistan Stock Exchange (PSX). Hypotheses were tested through the structural equation modeling (SEM) technique.

The article provides further insights into the relationship between recognition-based heuristic-driven biases and investment management activities. The results suggest that recognition-based heuristic-driven biases have a markedly positive influence on investment decision-making and negatively influence the investment performance of individual investors. The results also suggest that fundamental and technical anomalies mediate the relationships between the recognition-based heuristic-driven biases on the one hand and investment management activities on the other.

The results of the study suggested that investment management activities that rely on recognition-based heuristics would not result in better returns to investors. The article encourages investors to base decisions on investors' financial capability and experience levels and to avoid relying on recognition-based heuristics when making decisions related to investment management activities. The results provides awareness and understanding of recognition-based heuristic-driven biases in investment management activities, which could be very useful for decision-makers and professionals in financial institutions, such as portfolio managers and traders in commercial banks, investment banks and mutual funds. This paper helps investors to select better investment tools and avoid repeating the expensive errors that occur due to recognition-based heuristic-driven biases.

The current study is the first to focus on links recognition-based heuristic-driven biases, fundamental and technical anomalies, investment decision-making and performance of individual investors. This article enhanced the understanding of the role that recognition-based heuristic-driven biases plays in investment management. More importantly, the study went some way toward enhancing understanding of behavioral aspects and the aspects' influence on investment decision-making and performance in an emerging market.

The purpose of this paper is to elaborate the picture of strategies and tactics for information seeking and searching by focusing on the heuristic elements of such strategies and tactics.

A conceptual analysis of a sample of 31 pertinent investigations was conducted to find out how researchers have approached heuristics in the above context since the 1970s. To achieve this, the study draws on the ideas produced within the research programmes on Heuristics and Biases, and Fast and Frugal Heuristics.

Researchers have approached the heuristic elements in three major ways. First, these elements are defined as general level constituents of browsing strategies in particular. Second, heuristics are approached as search tips. Third, there are examples of conceptualizations of individual heuristics. Familiarity heuristic suggests that people tend to prefer sources that have worked well in similar situations in the past. Recognition heuristic draws on an all-or-none distinction of the information objects, based on cues such as information scent. Finally, representativeness heuristic is based on recalling similar instances of events or objects and judging their typicality in terms of genres, for example.

As the study focuses on three heuristics only, the findings cannot be generalized to describe the use of all heuristic elements of strategies and tactics for information seeking and searching.

The study pioneers by providing an in-depth analysis of the ways in which the heuristic elements are conceptualized in the context of information seeking and searching. The findings contribute to the elaboration of the conceptual issues of information behavior research.

The purpose of this paper is to develop a typology of heuristics in business relationships. We distinguish between four categories: (1) general heuristics used in the context of a business relationship but that may also (and are often) used in other contexts; (2) relational context heuristics that are typically used in a relational context; (3) relational information heuristics that rely on relational information and (4) genuine relational heuristics that use relational information and are applied in relational contexts.

We draw on existing literature on heuristics and business relationships to inform our conceptual paper.

We apply this typology and discuss specific heuristics that fall under the different categories of our typology. These include word-of-mouth, tit-for-tat, imitation, friendliness, recognition and trust.

We contribute to the heuristics literature by providing a novel typology of heuristics in business relationships. Emphasizing the interdependence between heuristics and business relationships, we identify genuine relational heuristics that capture the bidirectional relationships between business relationships and heuristics. Second, we contribute to the business relationships literature by providing a conceptual framework for understanding the types of heuristics managers use in business relationships and by discussing examples of specific heuristics and how they are applied in relational contexts.

We contribute to practice by providing a simple framework for making sense out of the “universe” of heuristics for business relationships.

Our paper provides a novel typology for understanding heuristics in business relationships.