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Literature review is considered as one of the most crucial section of a research study. This part of dissertation reviews the opinion of various scholars with respect to particular topic which is presented in an appropriate way. This tool of the study helps the researcher in examining the research data to analyze the facts, figures and studies related to the topic. Past literature and researches are evaluated to carry out the specific study. Present research will focus on developing theoretical base for this study in this segment of the research. The researcher has adopted secondary research method to evaluate and analyze relevant data and matter related to wisdom of crowd in order to create a definite learning method and seek appropriate opinions of various authors and researchers. It will focus on analyzing the appropriate analysis about the topic to carry out the further research.

Concept and definition

According to Kittur and Kraut, (2008) human being is a social animal who lives in a group and makes social relations and bonding to enhance his/her knowledge, relations and bonds within the society. Learning and development is an ongoing process for a person who develops the understanding and critical thinking of an individual. According to Golub and Jackson, (2010) every person has distinctive identity and individual thinking which helps him/her in making decisions and developing opinions as well. These opinions are then collected and analyzed to create a definite impact on knowledge and understanding of a person. Marbach and, 2012 discovered that collective opinions of crowds helps in making effective ways of decision making which in-turn assists in attaining conclusion for making developing effective understanding about the given problem.

Zesch and Gurevych, (2010) defines wisdom of crowd as a collective opinion of a group of individuals for making a common opinion about the subject or given problem. This measure helps in creating an effective impact on the growth and development of society by enhancing the knowledge of individuals influenced from the collective opinions. This method uses aggregate answers for the stated questions involving quantity estimations, general inquiries or queries related to reasoning. The aggregate answers to the given question is considered and analyzed for making decisions or developing opinion about the given subject.

The term wisdom of crowd according to Mannes, (2009) has its own significance and relevance. The crowd word used in the process refers to group of people who may belong to various disciplines, department or background. These are the people who respond to surveys, queries or who contribute their opinion for specific problem or issue. They may be group of experts, researchers, corporate or public as well. Social cohesiveness is not demanded in the process thus people responding to questions may be every random individual.

Types of Crowd

Crowd Wisdom is the process of taking into account the collective opinion of a group of individuals rather than a single person to answer a question. Leslie, (2010) has defined various crowds which help in making effective decisions for the given problems within an organization. This helps in creating an effective impact on studies which could help analysts in organizing the data to get required data for the same. The three major types of crowd groups defined are cognition, coordination and cooperation (Leslie, 2010). These three groups vary in the basic characteristics and qualities which enhances the decision making of a group or an individual as well.

Cognition is a crowd wisdom which is one of the fastest and most effective measures of analysis. Market judgment which arises for the product, service or policy is free and relevant to current state of the environment. This helps in developing critical thinking and enhances the decision making process of the companies as well (Lorenz and, 2011). Group of experts or expert committees deliberately participate in the process which enhances the success prospects for the same

Coordination is yet another type of group behavior which helps in analyzing social behavior in an appropriate way to create an effective understanding of the given subject or analysis as well. This segment helps in making corrective decisions and makes maximum utilization of logical decisions to enhance benefits from the subject. This creates an effective impact on the total analysis to create a common understanding (Gaissmaier and Marewski, 2011). This segment works with the people who shares a common culture and creates a definite impact on common behavior and opinions. Common understanding within a culture allows remarkably accurate judgments about specific reactions of other members of the culture.

Cooperation is the type where people develop group without any specific central system by controlling their behavior of needs. These groups are not enforced to comply with a particular structure or culture thus it helps in developing their own individual opinions and attributes for issues and problems prevailing within the market. These groups help in defining a well-developed segment of understanding the group impact on the growth of the community within the environment (Chen, Hu and Hwang, 2014). The above mentioned crowd wisdom helps in developing a specific impact on the decision making system of people and develop the similar views and opinions within the economy as compared to individual decisions

Conditions for the crowd to be wise

Researchers have often argued and questioned upon the conditions that helps in the success of wisdom of crowd. These conditions often help in delivering desirable results for the companies, society or industries to implement these measures. It helps them to gain appropriate results within the market. Various researches and studies have been conducted to create final impact of the same on overall understanding of the given study. The group thinking and presence of knowledge is one of the most significant factors for attaining positive result. Expertise and diversity are the two factors which evaluates the degree, to which crowds are more accurate than individuals

Yampolskiy and El-Barkouky, (2011) mentions that a crowd needs to involve individuals with some knowledge or expertise about the issue for resolving the question or business issues. This could be based on past education or experience. Crowd is formed of individuals with certain knowledge and understanding or expertise about the issues mentioned. This measure will help in making effective predictions about the uncertain knowledge on the basis of evidence to gain effective evidences about the given study or situation. This helps in developing valid judgments over the stated problems or questions which are prevailing

Marketing team from different segment will share better understanding about the problem thus will help the firm in developing better results in favor of growth and development of the company while minimizing chances of error. Kozinets, Hemetsberger and Schau, (2008) suggested two ways to foster diversity which are composition of the group and the other ne is process of sharing the information. This helps in developing an effective impact on the success of crowd wisdom and developing which in-turn helps in making better decisions.

Comparing crowd with an individual expert

The arguments regarding individual expertise and crowd wisdom has always managed to attract the attention of people within the market. Walter and Back, (2010) explains that the flaw in effective composition of the crowd or adopting improper process of distribution may result in ineffective results which may lead to wrong decision making. This has caused one of the major issues within the segment. Moreover, the comparison of crowd wisdom is tough as the resultant is more factual than implacable. On the other hand Nam, (2010) stated in the researches that individual expertise is widely trusted and values by organization as these are the quick and reliable sources of information. The identification of expertise helps in developing emotional factors such as trust and loyalty among people which results in developing confidence for these measures.

Ashby and Yampolskiy, (2011) examined that, identification of an individual may develop efficient barrier as the performance of a person vary according to situation and tasks. Moreover, the level of knowledge of an individual is limited which may not be applicable in every given situation this creates an effective impact on understanding of the subject and may get influenced by restrictive factors at times. These may be human emotions, stress or distraction. Thus, individual expertise has been replaced with wisdom of crowd to gain valid and reliable solutions within the current competitive era. Researchers have proven that the sum of average opinion is more reliable than choosing a single expert. The group of experts results in minimizing chances of errors for the process which helps in drawing a valid conclusion for the given problem. Moreover, varying abilities and efficiency is tough to examine thus average recommendation is comparatively relied more than the former. Furthermore, the process is convenient for gaining varied viewpoints which may help the organization in taking appropriate decisions for the prevailing problems within the market or economy.

Factors resulting in failure of crowd intelligence

Wisdom of crowd theory explains efficiently that a larger group of diverse people can helps in making better and effective decisions and displays higher level of intelligence as compared to small group of experts. The theory has been proven and defined efficiently by different researchers and scholars. However according to Murr, (2011) the theory has certain limitations for success within the market which may lead to the failure of crowd intelligence. These may impact few or mode decisions depending on the following and popularity of subject within the market. These factors have helped researchers in creating a valid and crucial impact on overall development of the company. Kittur and Kraut, (2008) has mentioned the following measures for the same

Inflexibility and bureaucracy are few relative measures which results in restricting or modifying opinions or free will of employees or group of people. Strongly centralized measures results in contaminating opinions of the group members as the decision making power is in the hands of senior authority. Wide levels of hierarchy results in deteriorating free flow of information and infect better understanding of the same within the group members which in-turn results in infusing biasness in crowd intelligence. This factor results in the failure of crowd intelligence which is affected by the centralization factor.

To develop effective intelligence of the crowd Walter and Back, (2010) mentions that proper access to correct information is one of the most significant factor which helps in developing views and opinions among people. These elements help in enhancing the growth and development of individual thing and thus create common group thinking. Further, widely divided groups and inefficient measures of communication create wide restriction on effective access of information at the given time. This results in delaying the process of thinking and delivering ineffective impact on overall process of behavior (Crowd Wisdom, 2015). It has been analyzed that, US intelligence agency failed to prevent the 11/9 attack partly because the information was widely Scattered which made it inaccessible by the group members

To develop effective intelligence of the crowd Walter and Back, (2010) mentions that proper access to correct information is one of the most significant factor which helps in developing views and opinions among people. These elements help in enhancing the growth and development of individual thing and thus create common group thinking. Further, widely divided groups and inefficient measures of communication create wide restriction on effective access of information at the given time. This results in delaying the process of thinking and delivering ineffective impact on overall process of behavior (Crowd Wisdom, 2015). It has been analyzed that, US intelligence agency failed to prevent the 11/9 attack partly because the information was widely Scattered which made it inaccessible by the group members

One more factor which results in decreasing the effectiveness of crowd intelligence is information cascade. This is a phenomenon where a group of people has gained something by making a particular decision in a given situation and resources. This may result in developing an effective range of copying where the people expect the similar results on the basis of previous experience or result expected. This creates a wide range of distraction and ineffectiveness in the group thinking and development of individual opinions. Moreover, the researchers have observed the impact resulting in misleading behavior of people and thus creating biased choices of individuals.


The above study helps to clearly define the values and measures that are taken for developing corrective decisions by individuals and organizations as well. These factors help in analyzing the impact of growth and development of the company on the basis of effective decisions which are availed from wisdom of crowd as per the study. The project focuses on analyzing following objectives:

  • Whether following the majority has a positive outcome on choice efficiency and social benefit
  • Does the free market solve coordination problem of following the crowd or does the public sector have to intervene

The above study developed in-depth knowledge and understanding about the given subject which helped in expanding the knowledge about the subject. The research report helped in evaluating factors which impact the decision making process of individuals and helps in developing a valid impact on the growth and development of set outcomes (Crowd-wisdom fails businesses. 2010). Various studies and examples have helped the researchers in learning the impact of wisdom of crowd on decision making process of an individual or business

Various examples and practical problems have assisted in developing an effective understanding about the given subject. Theories have proved that the aggregate or average results of the crowd have higher probability of right solution as compared to the later (Kozinets, Hemetsberger and Schau, 2008). “Who want to be the millionaire” is a valid example for the same where the contestants chose audience poll for making better decisions as compared to phone of friend where one expert solution was expected. The statistics of favorable solution was 65% for phone of friend and 91% for ask the audience (Wisdom of Crowds, 2008). Thus, this clearly proves that the traditional measures of problem solving are taken over by crowd of wisdom in the present era. Many other such examples have been stated where the decision making through wisdom of crowds have helped in making corrective decisions

According to Ashby and Yampolskiy, (2011) wisdom of the crowd is the most effective concept in determining efficient decision making. The organizations and markets implement the same in order to analyze trends and demand prevailing in the market. Free market is the one where government intervention is the minimum in the organizational decisions. This helps the units in attaining set objectives for the same. McFadden and Venker Weidenbenner, (2010) stated in one the study that the decision making process in a free market economy is taken on the basis of demand and supply theories. Government intervention is the minimum in this process as decision making in free market is based on aggregate demand within the market which may be evaluated by implementing wisdom of crowd. The expert panel of marketing heads may help in taking decisions and thus need of government intervention is minimum unless the product and services are sensitive to safety and security of the nation.


Books and Journals

    • Ashby, L. H. and Yampolskiy, R. V., 2011. Genetic algorithm and Wisdom of Artificial Crowds algorithm applied to Light up. In IEEE Intelligent Systems. pp. 27-32
    • Chen, H., De, P., Hu, Y. J. and Hwang, B. H., 2014. Wisdom of crowds: The value of stock opinions transmitted through social media. Review of Financial Studies. 27(5). pp. 1367-1403.
    • Gaissmaier, W. and Marewski, J. N., 2011. Forecasting elections with mere recognition from small, lousy samples: A comparison of collective recognition, wisdom of crowds, and representative polls. Judgment and Decision Making. 6(1). pp. 73-88
    • Golub, B. and Jackson, M. O., 2010. Naive learning in social networks and the wisdom of crowds. American Economic Journal: Microeconomics. Pp. 112-149
    • Kittur, A. and Kraut, R. E., 2008. Harnessing the wisdom of crowds in wikipedia: quality through coordination. In Proceedings of the 2008 ACM conference on Computer supported cooperative work. pp. 37-46
    • Kozinets, R. V., Hemetsberger, A. and Schau, H. J., 2008. The wisdom of consumer crowds collective innovation in the age of networked marketing. Journal of Macromarketing. 28(4). pp. 339-354
    • Leslie, M. B., 2010. The Wisdom of Crowds? Groupthink and Nonprofit Governance. Florida Law Review. (62). pp. 1179
    • Lorenz, J., and, 2011. How social influence can undermine the wisdom of crowd effect. Proceedings of the National Academy of Sciences. 108(22). pp. 9020-9025
    • Mannes, A. E., 2009. Are we wise about the wisdom of crowds? The use of group judgments in belief revision. Management Science. 55(8). pp. 1267-1279
    • McFadden, S. and Venker Weidenbenner, J., 2010. Collaborative tagging: traditional cataloging meets the “wisdom of crowds”. The Serials Librarian. 58(1-4). pp. 55-60
    • Murr, A. E., 2011. “Wisdom of crowds”? A decentralised election forecasting model that uses citizens’ local expectations. Electoral Studies. 30(4). pp. 771-783.
    • Nam, T., 2010. The Wisdom of Crowds in Government 2.0: Information Paradigm Evolution toward Wiki-Government. AMCIS. pp. 337.
    • Walter, T. P. and Back, A., 2010. Crowdsourcing as a Business Model: An exploration of emergent textbooks harnessing the wisdom of crowds. Proceedings of the 23rd Bled eConference, Bled, Slovenia. pp. 555-568.
    • Yampolskiy, R. V. and El-Barkouky, A., 2011. Wisdom of artificial crowds algorithm for solving NP-hard problems. International Journal of Bio-Inspired Computation. 3(6). pp. 358-369.
    • Zesch, T. and Gurevych, I., 2010. Wisdom of crowds versus wisdom of linguists–measuring the semantic relatedness of words. Natural Language Engineering. 16(01). pp. 25-59


  • Crowd Wisdom. 2015. [Online]. Available through: <> [Accessed on 15th October 2015].
  • The "Dumbness of Crowds". 2007. [Online]. Available through: <> [Accessed on 15th October 2015].
  • Wisdom of Crowds. 2008. [Online]. Available through: <> [Accessed on 15th October 2015].

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