Abstract:a b s t r a c tThe Wisdom of the Crowd advocates that decisions collectively made by a diverse crowd could be better than those made by an elite group of experts. The Wisdom of the Crowd puts preconditions on this to work correctly. This concerns the diversity of the crowd, their independence from each other, their decentralisation, and the methods of aggregating their distributed knowledge and forming collective decisions. Although the concept is inspiring, its interpretation and conduct differ significantly … Show more
“…According to social impact theory, the larger the group the greater its impact (Latané, ), so with the crowd size becoming too large, it is easy for crowd members to conform to the majority opinion. Therefore, we hypothesize the following:H5: Crowd size moderates the positive effect of participant independence on crowd performance; that is, participant independence exerts a more positive influence on crowd performance for a larger crowd.Decentralization prevents crowds from being dependent on a central reference point (Hosseini et al, ) by enabling crowds to obtain benefits through utilizing lower‐level users whose capabilities are often neglected in centralized decision crowds (Ashmos et al, ). Therefore, decentralization is considered to be positively associated with crowd performance (Richardson et al, ).…”
Section: Research Frameworkmentioning
confidence: 99%
“…Decentralization is often associated with a modular organizational structure (Helfat & Eisenhardt, 2004). A structural hierarchy is inevitable for enterprises; however, it has to be kept to a minimum for maximizing crowd wisdom (Hosseini et al, 2015). Structure decentralization has a positive influence on organizational functioning (Richardson, Vandenberg, Blum, & Roman, 2002), as it allows organizations to obtain benefits by taking advantage of lower-level employees whose capabilities are often neglected in centralized decision organizations (Ashmos, Mcdaniel, & Duchon, 1990).…”
Section: The Effect Of Network Decentralization On Crowd Performancementioning
confidence: 99%
“…Decentralization prevents crowds from being dependent on a central reference point (Hosseini et al, 2015) by enabling crowds to obtain benefits through utilizing lower-level users whose capabilities are often neglected in centralized decision crowds (Ashmos et al, 1990). Therefore, decentralization is considered to be positively associated with crowd performance (Richardson et al, 2002).…”
Section: The Moderating Effect Of Crowd Sizementioning
Fueled by the explosive growth of Web 2.0 and social media, online investment communities have become a popular venue for individual investors to interact with each other. Investor opinions extracted from online investment communities capture “crowd wisdom” and have begun to play an important role in financial markets. Existing research confirms the importance of crowd wisdom in stock predictions, but fails to investigate factors influencing crowd performance (that is, crowd prediction accuracy). In order to help improve crowd performance, our research strives to investigate the impact of crowd characteristics on crowd performance. We conduct an empirical study using a large data set collected from a popular online investment community, StockTwits. Our findings show that experience diversity, participant independence, and network decentralization are all positively related to crowd performance. Furthermore, crowd size moderates the influence of crowd characteristics on crowd performance. From a theoretical perspective, our work enriches extant literature by empirically testing the relationship between crowd characteristics and crowd performance. From a practical perspective, our findings help investors better evaluate social sensors embedded in user‐generated stock predictions, based upon which they can make better investment decisions.
“…According to social impact theory, the larger the group the greater its impact (Latané, ), so with the crowd size becoming too large, it is easy for crowd members to conform to the majority opinion. Therefore, we hypothesize the following:H5: Crowd size moderates the positive effect of participant independence on crowd performance; that is, participant independence exerts a more positive influence on crowd performance for a larger crowd.Decentralization prevents crowds from being dependent on a central reference point (Hosseini et al, ) by enabling crowds to obtain benefits through utilizing lower‐level users whose capabilities are often neglected in centralized decision crowds (Ashmos et al, ). Therefore, decentralization is considered to be positively associated with crowd performance (Richardson et al, ).…”
Section: Research Frameworkmentioning
confidence: 99%
“…Decentralization is often associated with a modular organizational structure (Helfat & Eisenhardt, 2004). A structural hierarchy is inevitable for enterprises; however, it has to be kept to a minimum for maximizing crowd wisdom (Hosseini et al, 2015). Structure decentralization has a positive influence on organizational functioning (Richardson, Vandenberg, Blum, & Roman, 2002), as it allows organizations to obtain benefits by taking advantage of lower-level employees whose capabilities are often neglected in centralized decision organizations (Ashmos, Mcdaniel, & Duchon, 1990).…”
Section: The Effect Of Network Decentralization On Crowd Performancementioning
confidence: 99%
“…Decentralization prevents crowds from being dependent on a central reference point (Hosseini et al, 2015) by enabling crowds to obtain benefits through utilizing lower-level users whose capabilities are often neglected in centralized decision crowds (Ashmos et al, 1990). Therefore, decentralization is considered to be positively associated with crowd performance (Richardson et al, 2002).…”
Section: The Moderating Effect Of Crowd Sizementioning
Fueled by the explosive growth of Web 2.0 and social media, online investment communities have become a popular venue for individual investors to interact with each other. Investor opinions extracted from online investment communities capture “crowd wisdom” and have begun to play an important role in financial markets. Existing research confirms the importance of crowd wisdom in stock predictions, but fails to investigate factors influencing crowd performance (that is, crowd prediction accuracy). In order to help improve crowd performance, our research strives to investigate the impact of crowd characteristics on crowd performance. We conduct an empirical study using a large data set collected from a popular online investment community, StockTwits. Our findings show that experience diversity, participant independence, and network decentralization are all positively related to crowd performance. Furthermore, crowd size moderates the influence of crowd characteristics on crowd performance. From a theoretical perspective, our work enriches extant literature by empirically testing the relationship between crowd characteristics and crowd performance. From a practical perspective, our findings help investors better evaluate social sensors embedded in user‐generated stock predictions, based upon which they can make better investment decisions.
“…It is denoted that for the wisdom of the crowd to work, four aspects of crowd diversity, independence amongst crowd members, decentralisation, and aggregation of the crowd knowledge must be considered. However, each of these aspects introduce their own benefits and challenges [31] which must be addressed by requirements engineers in any requirements monitoring framework used in this phase.…”
Abstract-Transparency is one of the main requirements in business information systems with its unique characteristics, and it requires designated engineering approaches. Despite that, transparency requirements have often been studied along other mainstream requirements relating to information, such as privacy, and seldom studied as a first-class concept. In addition, the literature on transparency is mainly driven by the perspective of information providers, and a large number of stakeholders who receive or request information are usually neglected. To achieve a holistic and more efficient management of transparency requirements, we propose a conceptual framework which integrates three mechanisms of crowdsourcing, structured feedback and social adaptation. Crowdsourcing facilitates the involvement of a large, diverse group of stakeholders in transparency engineering. The use of structured feedback helps automating the process of feedback acquisition and analysis. Eventually, as transparency requirements evolve over time, social adaptation can be applied to adapt the business information system to meet the emerging transparency requirements of the stakeholders.
“…Our understanding of wisdom involves a subtle handling of context. In contrast, WOC refers to a practice of gathering the input from a large amount of users who can bring a wide range of expertise, experience and aggregation methods to a scenario [8]. Applications of the WOC include using a wide range of inputs to filter internet content and improve the results of a search engine [20].…”
Abstract. This paper explores how the very human notion of Wisdom can be incorporated in the different behvaiour and ultimately reasonings of our computational systems. In particular, it extends and combines previous work in the areas of Computational Trust, Socially Adept Technologies, Device Comfort and the more recent notion of Slow Computing that was teased out at a recent Dagstuhl seminar. A brief exposition of Wisdom, its place in autonomous sociotechnical systems, and pointers to how we can make it work are provided. Further work is explored.
On Being Wise, and What it Might Mean for Computersthe only real wisdom is knowing you know nothing.Socrates 4 As humans, we value wisdom. It provides, in those who possess it, a knowledge of how things should be done, how life should be lived -either to the full or in some way that has less impact on, or is more in touch with, the world and society around it. Its gift is the ability to adapt to new, unforeseen, unexpected happenings gracefully, putting into practice experience in order to manage that which has not been encountered before.Computers and computational systems do not (presently) possess wisdom. It is an unerringly 'natural' phenomenon. 5 However, we believe that there may be something to be gained from its study, and ultimately the ability to incorporate the behaviours and reasoning into (at least semi-) autonomous computational systems can bring benefit. This short paper begins the exploration of wisdom and suggests ways in which Computational Wisdom might be achieved. It begins with an exploration of wisdom in the natural world (which includes people), and searches for common traits. It then delves into how these traits can be identified and aimed for in our computational systems, before beginning 4 A possibly equally old saying has it that Wisdom is knowledge that you gain immediately after you need it. . . 5 While there may be some debate, for which this is almost certainly not the right venue, there appears to be evidence that suggests that other animals than humans may possess it [9]
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