مقاله انگلیسی رایگان در مورد نحوه طراحی و مدیریت مدل های کسب و کار بر اساس جمعیت
مشخصات مقاله | |
عنوان مقاله | Leveraging collective intelligence: How to design and manage crowd-based business models |
ترجمه عنوان مقاله | توانمند سازی هوش جمعی: نحوه طراحی و مدیریت مدل های کسب و کار مبتنی بر جمعیت |
فرمت مقاله | |
نوع مقاله | ISI |
سال انتشار | |
تعداد صفحات مقاله | ۹ صفحه |
رشته های مرتبط | مدیریت |
گرایش های مرتبط | مدیریت کسب و کار MBA |
مجله | افق های تجارت – Business Horizons |
دانشگاه | مرکز مدیریت بین المللی و اقتصاد دانش فروانوفر، آلمان |
کلمات کلیدی | کسب و کار مبتنی بر جمعیت، مدل ها؛ جمع سپاری، ایجاد ارزش، ارزش جمعیت، هوش جمعی، استراتژی های ارزش آفرینی |
کد محصول | E4722 |
تعداد کلمات | ۴۹۱۲ کلمه |
نشریه | نشریه الزویر |
لینک مقاله در سایت مرجع | لینک این مقاله در سایت الزویر (ساینس دایرکت) Sciencedirect – Elsevier |
وضعیت ترجمه مقاله | ترجمه آماده این مقاله موجود نمیباشد. میتوانید از طریق دکمه پایین سفارش دهید. |
دانلود رایگان مقاله | دانلود رایگان مقاله انگلیسی |
سفارش ترجمه این مقاله | سفارش ترجمه این مقاله |
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۱٫ Crowds as value creators: New possibilities
Practitioners and researchers increasingly have identified crowdsourcing as a viable strategy to gather creative ideas and solutions, make decisions, and outsource small tasks (Prpic´, Shukla, Kietzmann, & McCarthy, 2015). So far, the focus has been primarily on how firms can capture the aggregated wisdom of the crowd (Surowiecki, 2005) for their business challenges. Over recent years, however, firms from different industries have started to develop new business models that fundamentally integrate crowds in value creation logic. The emergence of these crowd-based business models is both driven by advances in internet-based technologies (Kietzmann, Hermkens, McCarthy, & Silvestre, 2011) and a shift in the role of consumers toward becoming so-called ‘prosumers’ (Ritzer, 2014). Crowd-based business models (CBBMs) are generally characterized by (1) the integration of contributors from outside the traditional firm boundaries, (2) the exploitation of technologies such as digital peer-to-peer platforms, and (3) the transfer of value creating activities to a crowd (Kohler, 2015). This requires the firm to open certain resources and processes to external contributors, often resulting in a strong interaction with these contributors and their resources. The activity of these contributors can range from conducting microtasks to creating and delivering entire products and services to the firm’s customers. In this sense, CBBMs place even more importance on the crowd than traditional forms of crowdsourcing (Kohler, 2015). Due to their inherent value co-creation with crowds, CBBMs can lead to novel and superior value propositions. Wikipedia is a case in point. Originally considered a lower-cost and lower-quality alternative to established encyclopedias,the founding team has built effective systemsto engage and use a crowd of content contributors to review and update its articles constantly. As such, the platform soon developed into an exclusively comprehensive and upto-date source of information. The rise of Wikipedia provided an initial confirmation of the power of collective intelligence for crowd-based value creation. Le´vy (1997, p. 13) defines collective intelligence as: A form of universally distributed intelligence, constantly enhanced, coordinated in real time, and resulting in the effective mobilization of skills.. . The basis and goal of collective intelligence is mutual recognition and enrichment of individuals rather than the cult of fetishized or hypostatized communities. In simple terms, the concept of collective intelligence builds on the idea that ‘‘[n]o one knows everything, everyone knows something’’ (Le´vy, 1997, p. 13). As Wikipedia and other examples have shown, there exists a large potential for organizations to leverage the intelligence of individuals outside their boundaries. Or, as Sun Microsystem’s co-founder Bill Joy aptly formulated in what is now known as Joy’s Law: ‘‘No matter who you are, most of the smartest people work for someone else’’ (Lakhani & Panetta, 2007, p. 2). |