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A fundamental problem for intelligent manufacturing is to equip the agents with the ability to automatically make judgments and decisions. This paper aims to introduce the basic principle for intelligent crowds in an attempt to show that crowd wisdom could help in making accurate judgments and proper decisions. This further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.

Efforts to support the critical role of crowd wisdom in intelligent manufacturing involve theoretical explanation, including a discussion of several prevailing concepts, such as consumer-to-business (C2B), crowdfunding and an interpretation of the contemporary Big Data mania. In addition, an empirical study with three business cases was conducted to prove the conclusion that our ideas could well explain the current business phenomena and guide the future of manufacturing.

This paper shows that crowd wisdom could help make accurate judgments and proper decisions. It further shows the positive effects that crowd wisdom could bring to the entire manufacturing process.

The paper highlights the importance of crowd wisdom in manufacturing with sufficient theoretical and empirical analysis, potentially providing a guideline for future industry.

This article examines the accuracy and bias inherent in the wisdom of crowd effect. The purpose is to clarify what kind of bias crowds have when they make predictions. In the theoretical inquiry, the effect of the accumulated absolute deviation was simulated. In the empirical study, the observed biases were examined using data from forecasting foreign exchange rates.

In the theoretical inquiry, the effect of the accumulated absolute deviation was simulated based on mathematical propositions. In the empirical study, the data from 2004 to 2011 were provided by Nikkei, which holds the “Nikkei Yen Derby” competition. In total, 3,657 groups forecasted the foreign exchange rate, and the first prediction was done in early May to forecast the rate at the end of May. The second round took place in June in a similar manner.

The average absolute deviation in May was smaller than that in June. The first round of prediction was more accurate than the second round one. Predictors were affected by the observable real exchange rate, such that they modified their forecasts by referring to the actual data in early June. An actuality bias existed when the participants lost their diverse prospects. Since the standard deviations of the June forecasts were smaller than those of May, the fact-convergence effect was supported.

This article reports novel findings that affect the wisdom of crowd effect—referred to as actuality bias and fact-convergence effect. The former refers to a forecasting bias toward the observable rate near the forecasting date. The latter implies that predictors, as a whole, indicate smaller forecast deviations by observing the realized foreign exchange rate.

The purpose of this paper is to determine whether the quality and reliability of websites’ content can be assessed through the lens of “wisdom of the crowds”. In particular as a case study the authors examine the information supplied over time on several prominent Israeli real estate websites.

The Israeli real estate market was selected for the study, since there are many large, popular and dynamic real estate websites that feature hundreds of thousands of ads, representing most of the supply of real estate properties in the country. The authors built an automatic, ontology-based system that downloaded advertisements from three selected websites every two weeks for a number of months and checked for changes in these advertisements over time. The authors conjecture that wisdom of the crowds is mostly reflected by the information changes on the websites, since they indicate the anticipated market trends. Hence the authors developed a number of statistical measures to comparatively analyse trends of information changes on these websites, and assess their reliability compared to the actual market data and tendencies.

The primary results suggest similar information change trends amongst all the websites. Surprisingly, although some properties did not sell over time, sellers generally did not lower their asking price and were willing to wait. Sellers even raised their asking price, apparently in anticipation of future price increases. Comparison of recurring trends among the websites with the trends of the real market during the same time period and a few months after reveals that wisdom of the crowds is only partially effective as an indicator and predictor of website content quality: it correctly reflects the fluctuation in demand, but not in the prices.

This study was conducted over a limited time period of five months, and only in several cities in Israel. Additionally, since buyers are not explicitly represented in these sites, their information behaviour was not analysed, although it undoubtedly influences information changes performed by the sellers.

The practical contribution of this study is the ontology of the real estate world. Its assimilation by real estate websites would promote the development of their sites and user services. It would also enable ad sharing amongst the various websites and enable efficient searches by search engines. In addition the tools and measures that the authors developed will allow continued monitoring and analysis of user information change patterns.

To the best of the knowledge this is the first study to examine and compare real estate websites’ quality and evaluate their information reliability as wisdom of the crowds.

One of the under-explored aspects in the process of user information seeking behaviour is influence of time on relevance evaluation. It has been shown in previous studies that individual users might change their assessment of search results over time. It is also known that aggregated judgements of multiple individual users can lead to correct and reliable decisions; this phenomenon is known as the “wisdom of crowds”. The purpose of this paper is to examine whether aggregated judgements will be more stable and thus more reliable over time than individual user judgements.

In this study two simple measures are proposed to calculate the aggregated judgements of search results and compare their reliability and stability to individual user judgements. In addition, the aggregated “wisdom of crowds” judgements were used as a means to compare the differences between human assessments of search results and search engine’s rankings. A large-scale user study was conducted with 87 participants who evaluated two different queries and four diverse result sets twice, with an interval of two months. Two types of judgements were considered in this study: relevance on a four-point scale, and ranking on a ten-point scale without ties.

It was found that aggregated judgements are much more stable than individual user judgements, yet they are quite different from search engine rankings.

The proposed “wisdom of crowds”-based approach provides a reliable reference point for the evaluation of search engines. This is also important for exploring the need of personalisation and adapting search engine’s ranking over time to changes in users preferences.

This is a first study that applies the notion of “wisdom of crowds” to examine an under-explored in the literature phenomenon of “change in time” in user evaluation of relevance.

The purpose of this chapter was to deconstruct the underlying contradictions of crowdfunding practices and to show how crowdfunding practitioners develop a schizophrenic use of these contradictions.

The main contradictions of crowdfunding practices are introduced with theoretical references. Then short cases are used to illustrate how crowdfunding practitioners try to cope with these contradictions.

The crowd addresses many contradictions, first because it is a syncretic concept, second because online crowds are still to be proven crowds. In any case, crowdfunding practitioners do their best to take the advantage of these contradictions, and run the risk of falling between two stools.

An attempt to provide an analysis of crowdfunding as a social, and not only economic, phenomenon, to suggest avenues for further critical research on crowdfunding.

An emerging management trend is to use the “wisdom of the crowd” to make decisions traditionally made by the top management alone. Research on this phenomenon has focused mainly on the capacity of crowds to generate ideas, but much less is known about a crowd’s capacity to select ideas. To study crowd-based idea selection in firms, this chapter develops a mathematical model of a crowd that makes decisions by majority voting. The model takes into account contingencies that are of particular importance to firms, namely: the size of the population from which the crowd is drawn, the distribution of accuracy among members of the population, and the firm’s ability to recruit the population’s most accurate individuals. The results show that: (1) under relatively common conditions, increasing the size of the crowd may actually reduce performance; (2) near-optimal performance can usually be achieved by a much smaller crowd than the one required to achieve optimal performance; (3) determining the best crowd size depends critically on the firm’s ability to recruit “accurate” individuals; and (4) good performance does not require large crowds unless all population members exhibit low levels of accuracy.

The aim of this paper is to define a framework for public information services in the twenty‐first century, as a means to address some arguments that are put forward in the debate on the obsoleteness of public information services in the age of the internet.

The paper discusses theoretical concepts on the function of information in modern democracy, followed by analysis of two foremost models of seeking knowledge, “the wisdom of crowds” and “expertise”, the different kinds of questions both forms apply to, the kind of knowledge the different models result in, and the application of the findings from that analysis in the information services environment.

The function of information in a modern democracy still applies today. Information is a means to allow citizens to make informed decisions in the democratic process. The debate on the proper way to provide functional information services in modern democracy is roughly divided between two “schools of thought”. One of them puts the model of “the wisdom of crowds” forward, and sees information technology as the final answer to all questions. The other relies on expertise, which is paramount in classic information services. The conclusion of this paper is that, where not all (research) questions yield to knowledge derived from the wisdom of crowds, there is a true need for information services that specialize in providing information produced by experts. As no other party provides that, public information services should commit themselves to playing a central role in society in providing expert information.

The main value of the paper is comprehensive analysis of the widespread claim that free information on the internet is the end to all means, providing all knowledge at the fingertips. It provides arguments to put forward in debates on the value of public information services.

Ontologies are defined as consensual formal conceptualisation of shared knowledge. However, the explicit overlap between diverse ontologies is usually very low since they are typically constructed by different experts. Hence, the purpose of this paper is to suggest to exploit “wisdom of crowds” to assess the maximal potential for inter-ontology agreement on controversial domains.

The authors propose a scheme where independent ontology users can explicitly express their opinions on the specified set of ontologies. The collected user opinions are further employed as features for machine classification algorithm to distinguish between the consensual ontological relations and the controversial ones. In addition, the authors devised new evaluation methods to measure the reliability and accuracy of the presented scheme.

The accuracy of the relation classification (90 per cent) and the reliability of user agreement annotations were quite high (over 90 per cent). These results indicate a fair ability of the scheme to learn the maximal set of consensual relations out of the specified set of diverse ontologies.

The data sets and the group of participants in our experiments were of limited size and thus the presented results are promising but cannot be generalised at this stage of research.

A diversity of opinions expressed by different ontologies has to be resolved in order to digitise many domains of knowledge (e.g. cultural heritage, folklore, medicine, economy, religion, history, art). This work presents a methodology to formally represent this diverse knowledge in a rich semantic scheme where there is a need to distinguish between the commonly shared and the controversial relations.

To the best of the knowledge this is a first proposal to consider crowd-based evaluation and classification of ontological relations to maximise the inter-ontology agreement.

This paper aims to explore the effect of participant composition and contribution behavior of the different types of participants on the quality of knowledge generation in online communities.

This study samples all the featured articles in Chinese Wikipedia and performs a Cox regression to reveal how participant composition and contribution behavior affect the quality of articles in different contexts.

The results show that an increase in the number of participants increases the possibility of either enhancing or reducing the article quality. In most cases, the greater the proportion of core members (people who frequently participate in editing), the higher the possibility of enhancing the article quality. Occasional participants’ editorial behavior hinders quality promotion, this negative effect weakens when such editorial behavior becomes more frequent.

The findings help to better leverage the role of online communities in practice and to achieve knowledge collaboration in a more efficient manner. For example, an appropriate centralized organizational form should be established in online communities to improve the efficiency of crowd contributions. And it is worth developing mechanism to encourage participants to frequently participate in editing the article.

This study contributes to the research on the organizational forms of online communities by showing the effect of participant composition and behavior in the new form of organizing on knowledge generation. This study also contributes to the research on wisdom of crowds by revealing who in a group of participants, in what context, and by what means influence knowledge generation.

The purpose of this paper is to portray an example of how organizations can harness their employees’ insight. The procedure described here can complement traditional methods such as interviews, open forums, round tables and employee surveys, and can assist HR managers to acquire a unique look inside the company.

The described procedure was facilitated at Intel Corporation and was about The Future of Work. 145 Intel employees took part in an online crowd-deliberation with a methodology called Real-Time Imen-Delphi (RTID). The methodology guided them to initiate 689 questions that were then organized into 258 mission statements, which were rated by importance, priority and feasibility.

A main theme was identified to represent the collective notion with regards to The Future of Work. The participants leaned toward the fractal model for a preferred work environment. This model includes employees who will no longer have a single job description, but rather repeatedly sign up for tasks and projects based on their interests, capabilities, availability, aspirations and future beliefs regarding the path their organization needs to take in manufacturing, research and development.

The result provides an example of how organizations can harness their employees’ wisdom to bring to the table cutting-edge ideas, debate their relevancy to the organization, agree collectively on their vision and generate applicable ideas toward realizing their preferred future.

As social media tools evolve and become a central part in organizations, they will seek to involve employees in effective conversations and in decision-making processes. RTID is a solid way with which they can do this.