A Methodology to Manage and Monitor Social Media ...

A Methodology to Manage and Monitor Social Media inside a Company: A Case Study

Alberghini, E., Cricelli, L., Grimaldi, M. (2014) "A methodology to manage and monitor social media inside a company: a case study", Journal of Knowledge Management, Vol. 18 No. 2, pp.255 – 277.

Keywords Case study, Collaboration, Individual participation, Key performance indicator, Knowledge Management, Knowledge sharing, Social media, Social media measurement, Social technology

Abstract Purpose – This paper aims to discuss the individual participation and involvement affecting the user engagement in social media and to answer the following research questions: Is it possible to measure the individual participation and involvement of social media within organizations? Which factors should be analysed in order to increase the individual participation in social media? Which KPIs should be selected in order to increase the user's engagement and increase individual participation in social media? Can social media in a company be measured in terms of their impact on KM? Design/methodology/approach – This paper presents a case study that describes how Key Performance Indicators (KPIs) are used to monitor and manage the applications of social technologies, which include many tools facilitating the participation and collaboration on the web. The case study was applied to the information and communication technology area of Eni S.p.A., which is an integrated energy company active in over 70 countries in the world. Findings – Based on the indications obtained from the case study, a methodology is proposed to select and develop the appropriate KPIs in order to manage and monitor the application of social technologies. The methodology turned out to be able to monitor collaboration and knowledge sharing activities among employees and to incentivize participation and involvement of employees who use the company's social media. Practical implications – Organizations can use the suggested methodology as a guideline for managing and monitoring social media inside a company. The possibility of continuously modifying the adopted social media tool by means of corrective actions together with the possibility of adapting the KPIs to new situations make the present methodology an efficient management approach to take on the multifaceted activities of a social media environment. Originality/value – Few case studies dealing with the applications regarding the implementation and management of social technologies within organizations have been carried out. Similarly, even if some empirical studies have been proposed to analyse what motivates and prevents employees from sharing their knowledge through social media, there appears to be a lack of studies which have taken into consideration the evaluation of the actual benefits in terms of individual involvement and participation, knowledge sharing and increase in performance.    

A Methodology to Manage and Monitor Social Media inside a Company: A Case Study

1. Introduction In recent years, social technologies have contributed to change modes and means that, until then, were adopted by people to collaborate and communicate for private and public use (Tailor, 2008). Soon after their first application, social media have caught the attention of organizations, communities and individuals through their ability to facilitate the collaboration of virtual communities and to provide a productive environment for mutual sharing and interaction (Corvello and Migliarese, 2007; Cheung and Lee, 2010; Kaplan and Haenlein, 2010; Levy, 2013). The implementation of Enterprise 2.0, which is the application of social technologies inside companies, offered individuals the possibility to become the focal representatives of their organizations due to their strong support in improving knowledge management (KM) techniques (Alberghini et al, 2010). The use of Enterprise 2.0 has shown to be able to improve the management of the knowledge-based assets and to facilitate the cognitive flows among organizational processes (Falsini et al., 2012; Marra et al., 2012). Organizations can achieve considerable advantages through the use of social technologies by enhancing the capability of integrating knowledge which is developed in different contexts. From this point of view, it has been proved that this kind of social interaction can support creativity, innovation and new product development (Culnan et al., 2010; Di Gangi et al., 2010; Calabrese et al., 2013). Moreover, social technologies play an important role in sustaining the processes which are a matter of interest to external stakeholders (Mangold and Faulds, 2009). An increasing number of companies are using social technologies to improve the interaction with external stakeholders in order to increase business values such as improving customer satisfaction and supplier loyalty, increasing sales and revenues,    

supporting marketing initiatives, creating brand awareness and reputation, enforcing loyalty performance (Culnan et al., 2010; Kietzmann et al., 2011; Sinderen and Almeida, 2011). Social media technologies are generally considered to be tools for business management, effectively designed and implemented for external use (Yates and Paquette, 2011). Regardless of their common external applications, only the internal use of social media and its measurement issues have been analysed in this paper. Both from the academic and the practical point of view, attention must be placed on the demarcation and evaluation of the new technologies and trends so that the real internal value of social media as a component of the modern KM can be determined (Constantinides and Fountain, 2008; Grimaldi et al., 2013). It is widely recognized that the internal use of social media helps employees fulfill their knowledge tasks and meet their objectives through informal interactions (Paroutis and Al Saleh, 2009). In a way internal KM applications of social media are close to some of the ideal principles of KM, which include the unrestricted sharing of knowledge, information, and data (Cricelli and Grimaldi, 2008; Levy, 2009; Razmerita et al., 2009; Mancini et al., 2012). Knowledge benefits deriving from the internal use of social media are basic and immediate, such as better handling of information throughout the organizational hierarchy, empowering individuals to create, share and search content, as well as to communicate and collaborate with each other. Most of the goals and end results of social media structures can be reached more quickly and more efficiently thanks to the benefits of KM (Choong, 2008; Cricelli and Grimaldi, 2010; Green and Ryan, 2005; Moeller, 2009). However, the benefits of social media do not affect only KM but also extend to information management at the various levels of operation strategies and of production processes (Falcone et al., 2010; Falcone et al., 2013). In particular, benefits include an overall increased productivity and output, a better innovation and implementation of new ideas and a better customer service. A shared interpretation of knowledge among operational personnel    

determines how knowledge is disseminated and used to design and implement a unified operational response to that knowledge (De Felice and Petrillo, 2012). Even though there appears to be evidence that suggests an increasing significance of these social technologies within the organization and a well recognizable growth of the real and potential benefits deriving from the use of social media, there is still no agreement about the methods that could help measure such benefits in literature. Consequently, there is a need to develop a methodology to better understand their effects and to measure and analyse employee involvement and requirements. First of all, organizations should evaluate the actual participation and usage of the social media by their employees. To this purpose, it is important not only to explain the user motivation but also to examine how the employee social relationships moderate media usage in the current job environment and, above all, to monitor and to support user engagement (Bowman et al., 2012; Picazo-Vela et al., 2012; De Felice and Petrillo, 2013). Moreover, organizations should understand the extent to which the usage of social media influences the task performance and allows increased benefits (Kahai and Cooper, 2003). At the same time organizations should measure the level of improvement in task performance caused by the integration of social media usage (Chang et al., 2009; Koo et al., 2011). In general, the measurement issue for social technologies has two possible objectives: first, the supporting activity of choosing the most appropriate tool from several solutions; second, the evaluation of the expected benefits and the determination of proof of return on investment from the social media effectively in use. In this paper, only the second evaluation issue is taken into consideration. It has been acknowledged that there is a need for more practical ground research in this field and that few case studies have dealt with the applications regarding the implementation and management of social technologies within organizations. Similarly, there appears to be a lack of studies which have considered the evaluation of the actual benefits in terms of individual involvement and participation, knowledge sharing and increase in performance. Accordingly,    

an extension of the previous work has been carried out in this paper, in which a methodology is described and applied to a case study in order to investigate the modalities of implementation of the social media within the organizations and to evaluate the benefits deriving from the internal use of social media. The methodology aims to define and apply the correct Key Performance Indicators (KPIs) to internal applications and technologies of social media within a company, with the main purpose of benefiting from knowledge sharing and user participation. A case study approach was used to test the defined methodology. The methodology was applied to Eni, an integrated and multinational energy company that considers KM as a key element in enabling the effective use of the available know-how and the professional development of its employees. Eni operates in oil and gas, electricity generation and sales, petrochemicals, oilfield service construction and engineering industries. The methodology was tested for Eni because for a long time this organization has invested in KM in order to improve the performance of its organization and production processes. The adoption of KM has shown to be particularly relevant for the oil and gas industry starting in the 90s. The determination to emphasise KM activities derived from the acknowledgement that the oil and gas industry is considered as a knowledge-based business and that competitive advantage depends upon the ability of a company to exploit knowledge more effectively than its competitors (Grant, 2007). The paper is organized as follows. Section 2 provides a literature review of social media, its internal use, its link with KM, and its measurement. Section 3 details the research questions. Section 4 presents the field of the study. Section 5 defines and analyses the methodology, which includes four specific steps: the definition of the strategic objectives, the rationalization process, the application and monitoring of measurements and, finally, the proposal of corrective actions. Section 6 describes the findings of the application of the methodology to the case study and the results of the research. Section 7 presents the conclusions of the paper.    

2. Theory development 2.1 Social Media The term “social media” refers to web-based and mobile technologies able to turn communication into an interactive dialogue. They include many different forms such as social networks, internet forums, weblogs, magazines, wikis, podcasts, videos, ratings and social bookmarking. All these technologies derive from the so-called “Web 2.0” (Kaplan and Haenlein, 2010). Web 2.0 is a collection of methodologies, technologies, social and business models, characterized by openness, participation, use of lightweight technologies and decentralized, distributed processes. All these practical applications facilitate interactive information sharing, interoperability, user-centered design and collaboration on the World Wide Web (Lee and Ma, 2011). The concept of using Web 2.0 technologies inside an organization is one of the aspects of the so called “Enterprise 2.0” phenomenon. The term “Enterprise 2.0” was first coined in 2006 by Andrew McAfee and later defined as the particular use of emergent social software platforms within companies, or between companies and their partners or customers (McAfee, 2006). In other words Enterprise 2.0 is related to the adoption of Web 2.0 technologies within an organization and favours the connection of employees through the use of social-media tools. Recent studies (Alberghini et al., 2013; Ferron et al., 2011; Koo et al., 2011) have highlighted several benefits that Enterprise 2.0 social technologies can bring to an organization. The usage of social media has resulted in improvements in work quantity and quality, and increased the awareness and acquisition of relevant information. There is clear evidence that it fosters transparency and collaboration while helping to promote knowledge sharing, as well as being capable of distributing it rapidly (Rice and Bair, 1984). What’s more, as hinted above, social media can increase the number of business positions as a consequence of their capability of creating brand awareness, personnel trustworthiness and of activating employee    

awareness. Furthermore, social technologies allow employees to work actively and have a thorough knowledge of their subjects of interest. As the world has become increasingly connected, the focus has shifted to augmenting social experience and collective intelligence (Hansen et al., 2010).

2.2 Internal use of Social Media The network concept has been widely applied in many operational fields mostly as a consequence of its intrinsic characteristic of combining relationships of different types and at different levels. Social media networks have become important ways to map and represent the relationships and connections among groups and employees of organizations through visualizations which express the real situation. Even if the nature of most social technologies opens companies to greater interactions with the outside world, plenty of research works have been deeply focused on the advantages derived by organizations from the internal adoption of social media (Greco et al., 2013a; Kietzmann et al., 2011). Research regarding applications within organizations has included the study of their role in individual involvement and adaptation to IT-induced change (Bruque, et al., 2008), in providing e-services, and in finding business opportunities (Wilson, 2009; Calabrese, 2012). Similarly, Goodhue and Thompson (1995) pointed out how users believe that technology has a more positive impact on their performance when they perceive the characteristics of such technology to match those of their tasks. However, it has been demonstrated that users tend to use multi-media rather than relying on one specific medium. Koo et al. (2011) suggested that the adoption of one or more social communications technologies should have a substantial impact on task performance. In this vein, many studies about the usage and measurement of media have attempted to create lists of uses and satisfactions (Quan-Haase and Young, 2010). Social media tools allow users to connect, inform, inspire, and track other employees in order to collaboratively create, find, share, and evaluate the available information. Thus social    

media can be considered as an internal support able to transform individuals from passive consumers of content to active producers of information (Nov et al., 2010) and also to create and maintain relationships with other individuals with similar needs, interests or problems (Cho et al., 2010; Lee and Ma, 2012). Users can receive personalized recommendations based on the prior experience of thousands of other counterparts, can collaboratively write a document and provide decision makers with feedback and suggestions about a professional report. But there is an undeniable threat in direct contrast with the numerous advantages deriving from the adoption of social media: the voluntary nature of the user to contribute to the common media tools. This brings us to the important issue of the user’s motivation to interact with such social media networks, essentially based only on decisions deriving from their personal use (Vuori and Okkonen, 2012). So there is a need to encourage the users to make use of social media by arousing their interest in the benefits achievable from doing so (Durugbo, 2012). The means and modalities of putting this kind of persuasiveness into effect are still debatable.

2.3 Social Media and Knowledge Management Knowledge sharing practices and the role of social media have jointly highlighted the need to update the meaning of KM. New theories and research are emerging with regard to how to modify knowledge processes such as creation, transfer, and capture by means of tools and technologies based on social media (Faraj et al., 2011; Haefliger et al., 2011) and to verify whether social media are revolutionizing how employees handle knowledge (Bebensee et al., 2011). In the past, KM was defined as organizational practices which facilitated and structured knowledge sharing among knowledge workers. However, apart from the evolution of the organizational structures, reward systems, and training programs, it seems to be necessary to have ICT tools available (Orlikowskj, 1996; Huysman and de Wit, 2004). It was believed by many that KM would be put into practice naturally in those situations where    

individuals benefited from sharing initiatives by making use of ICT (Alavi and Leidner, 2001; Bloodgood and Salisbury, 2001; Newell et al., 2002). In this evolution, social media are now recognized as tools that support group interaction among communities which create and exchange content by making reference to a conversational, distributed mode of knowledge generation and dissemination (von Krogh, 2012). Indeed, social media provide users with the ability to create and share common knowledge by setting up informal networks, increasing knowledge re-use by staff, and eliminating the reliance on formal liaison structures between members of staff (Awazu and Desouza, 2004). In particular, social technologies provide knowledge workers with the ability to react quickly to changes in information and environment, by “facilitating the flow of ideas and knowledge by allowing the efficient generation, dissemination, sharing and editing/refining of informational content” (Constantinides and Fountain, 2008, p. 231). As a result, social media content and tools, if transferred into organizations, could contribute to solve most of the KM gaps by making the KM assimilation within organizations easier (Levy, 2009). Internal KM usage of social media consists of a series of applications such as blogs, wikis, social bookmarking, data mashup, editing platforms, and media sharing, which are intuitive to understand and easy to use. More precisely, the application of social media for KM can be classified into five main categories (Constantinides and Fountain, 2008): web logs (online journals, i.e. the most known and fast-growing category of Web 2.0 applications); social networks (applications allowing users to create personal websites that are accessible to other users for exchange of personal content and communication); communities (websites organizing and sharing specific contents); forums/bulletin boards (sites for exchanging ideas and information usually regarding particular interests); content aggregators (applications allowing users to fully customize the web content they want to access). Consequently, the internal use of social media has several implications for KM activities. First of all, while networking may not be the primary motivator for their use, social media    

technologies allow knowledge sharing through the creation of informal users’ networks, thus allowing users to collaborate with each other starting from their points of view and perceptions and supporting the efficient generation, dissemination and sharing of informational content (Constantinides and Fountain, 2008). Moreover, social media provide users with the ability to create semantics and taxonomies useful to organizations and store this information for retrieval (Hendler and Golbeck, 2008) while quickly responding to changes in information and in environment. In addition, social media facilitate knowledge sharing, not only by increasing knowledge re-use, but also by eliminating the reliance on formal liaison structures in terms of personnel and systems (Yates and Pasquette, 2011). Moving on from the influence of social media on KM towards other social media returns, it is possible to state that social media can also have a strong impact on the efficiency and effectiveness of every business operation, by making use of as few resources as necessary and by meeting most customer requirements. All organizational processes could achieve real advantages from the application of social media networks within the organizations because of their ability to enhance and share knowledge at every level of the organization (Hansen and Nohria, 2004; Molina et al., 2007). Social media represent a prevalent source of useful information through which organizations can speed up the exchange of a significant amount of knowledge (Gopal and Mardsen, 2011). This is because the internal use of social technologies enhances both the content of the information used in the design, control and development of productive process, and the management of the information deriving from stakeholders. As for the first aspect, firms can decide to adopt social media on the grounds of their ability to meet the technical requirements and respond to community concerns regarding their innovation (Di Gangi and Wasko, 2009; Patel et al., 2012). Recent studies about business applications of social media show that disruption is inevitable (Christensen et al., 2013) but the use of social media can effectively support information sharing, communication and collaboration, in particular in times of crisis    

(Barchiesi et al., 2014; Billington, 2012; Dabner, 2012). Moreover, for many companies, social media will become the gateway communications channel to connect with customers (Christensen et al., 2006; Baird and Parasnis, 2011). Social media can achieve results by favouring a many-to-many collaboration, which goes beyond the one-to-many broadcast channels like television and radio. Some leading-edge brands have already understood that social media can facilitate many-to-many collaborations in order to engage a community and create a new kind of relationship with consumers (Goswami et al., 2013). In this context there is an increased use of social media and social networking sites by organizations (Sinclaire and Vogus, 2011). So, given the importance of applying social technologies to help and improve KM, it is important to be able to measure and analyse the use of social networks.

2.4 Social Media Measurement and KPIs The wealth and popularity of social media have encouraged researchers to study the different applications related to the use of social media within organizations and hypothesize potential measurements of the extent of their relationships (Picazo-Vela et al., 2012). Social media measurements refer to the tracking of their content in terms of volume, sentiment towards a brand or particular topics within the social media exchanges of opinions (Li and Bernoff, 2008). Over the last few decades, the amount of research being carried out regarding networks in organizations dealing with social media measurement has increased rapidly (Borgatti and Foster, 2003). It is important to emphasize how critical the analysis of web data is in order to measure the success of a social network within a company and how it cannot be done without making top management more sensitive and aware of the problem (Chang et al., 2009; Pantano and Corvello, 2013). Moreover, it is well known that it is difficult to measure the impact of social media on the organization because the measurement of social media network traffic refers to a very short-lived time frame as visitors usually visit one single page    

and quickly leave it (Yang, 2010). Very often companies have decided to measure the benefits and the characteristics of their social media tools by referring to KPIs. KPIs are quantifiable measurements and concise indicators designed to measure the achievement of strategic objectives by combining a lot of information (Davenport and Beck, 2000; Pavlou, 2005; Alberghini et al. 2013). KPIs are commonly used by an organization in order to analyse the critical success factors of a particular activity in which it is engaged. In a personalized and simple way, they help understand the trend of the business performance. Moreover, KPIs are able to highlight sudden changes that need immediate intervention. KPIs allow the measurement of the popularity of a portal and its name, a sort of brandawareness parameter for a specific theme; the number of content downloads from a specific portal and the number of links each portal provides. Moreover, the most common KPIs can provide the number of visits, number of visitors, and number of page views, as well as geographic locations (users’ country and city of origin) and number of hits. KPIs can also analyse other measurements of social media such as success and efficiency of their network, number of visits received through the established links with other websites, and can monitor the number of regular users of their services. The main KPIs proposed in literature to measure user participation and involvement are: accessibility to information; simplicity (how simple and understandable the information is); standardized data formats or application interfaces; distinctiveness (how distinctive the information is compared to other information); target-orientation (the specificity of the target which the initiative aims to directly influence); degree of involvement; measure of participation; cross-organizational interoperability; presence of practical rewards for stimulating the participation and for attracting new users by means of prizes or points (Butler, 2001; Frantz et al., 2005; Langley and van den Broek, 2010; Lin, 2006; Schaik and Ling, 2008).

   

Moreover, some research regarding KPIs has monitored the performance of the internal use of social media in KM. The main KPIs proposed in literature to measure the performance of KM processes, such as knowledge learning, knowledge sharing and knowledge applications concerned the following topics: personalization characteristics (the extent to which the information is presented in a personalized form or the extent to which the message shared with non-participants is personalized); usability and flexibility (information and knowledge are easy to use together, transparent and clear to use, and their user interfaces are welldesigned for the task); sharing simplicity (the extent to which sharing with non-participants is simple and easy to carry out); communication interactivity (the presence of options for reciprocal exchange of information); synchronicity (the presence of options for real-time reciprocal exchange of information); possibility of analysing and filtering data from different information sources; possibility of sharing and storing tacit and informal knowledge; system integration (the possibility for the organization’s information systems to be integrated rapidly and reliably); alignment between social media tools and business processes; integration of social media tools in business processes (Alavi and Leidner, 1999; Chung et al., 2005; Seo and La Paz, 2008; Koskinen et al., 2012). A critical feature of social media measurement is represented by the homogeneity of how user participation and involvement should be measured. In this respect, some KPIs have been proposed in literature, such as traffic data (the number of visits to the sites); follower data (representing the number of employees who are active in the various areas of the network and how they are growing); social interaction data (how many employees are interacting and sharing a particular content on social networks).

3. The research questions As described in the previous sections, KM can bring benefits to all of the organizational processes and support organizations in achieving a business strategy. Since knowledge is to a    

large extent tacit in nature and widely dispersed within the organizations, their long term competitiveness, when based on KM activities, depends almost entirely on their absorptive capacity and their learning capabilities (Cuellar et al., 2011). Moreover, the social network perspective focuses on the relationships among actors. People, when part of a team, tend to collaborate in organized relational patterns and accomplish their intended objectives in a collective manner (Zenk et. al., 2010). Therefore the modalities of their collaboration affect overall outcomes, such as both individual and group performance, and the degree of innovation and employee satisfaction (Brass, 2009). What helps the development of informal communication is the integration of social communication technologies within organizations. Social media help employees apply the SECI model proposed by Nonaka and Takeuchi (1995), which turns the socialization, externalization, conversion and integration of knowledge into operationalization. Thus social media can create a network capable of supporting expert workers in sharing their explicit knowledge and combining their tacit knowledge. It means that gaps in skills, competencies and knowledge within the organizations could be filled by social media through KM applications. It should also be observed how social media can be an important channel to external stakeholders for a variety of purposes, such as listening, information gathering, and communicating. Therefore organizations can assess the strategic implications of developing a platform. In view of the arguments presented above, the following questions motivate this research: 

Is it possible to measure the individual participation and involvement of social media within organizations?

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Which factors should be analysed for increasing individual participation in social media?

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Which KPIs should be considered in order to increase the user’s engagement and the increase in individual participation in social media?

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Can a company’s social media be measured in terms of their impact on KM?  

 

In order to answer these research questions this paper analyses social technology measurements through a theory-building case study. Indeed, based on the evidence deriving from the case study (Bailey and Francis, 2008; Barclay and Osei-Bryson, 2010; Browning and Heath, 2009; Staats et al., 2011), a methodology is proposed to select KPIs able to manage and monitor the application of social media. First of all the case study analyses the current situation in the early adoption stage of social technologies in Eni, as explained in Section 4. Then the four steps of the definition and application of the methodology are described in detail in Section 5. Finally the study analyses the findings of the application.

4. The field study: Eni Eni is an integrated energy company, operating in the sectors of oil and gas exploration & production, international gas transportation and marketing, power generation, refining and marketing, chemicals and oilfield services. Eni is active in 90 countries with a staff of about 79,000 employees. Eni has reported a consolidated net profit of €7,788 million and a market capitalization of €66.4 billion. The history of Eni and its companies is closely related to the economic development in Italy. It started in 1953 and can be traced back to the foundation of AGIP in 1926. In the energy sector, since the early 90s, different strategic priorities have influenced every company’s KM strategy, from cost reduction to best practice transfer, aiming to achieve greater coordination within decentralized organizational structures. Other reasons that suggest companies should implement KM systems include facilitating project archiving and general project management, capturing experiences associated with disaster recovery and back-up operations, refreshing technology and exploring future needs. For these reasons Eni represents a critical and extreme case (Eisenhardt, 1989) of a company which considers KM to be a key element in the company's intangible assets and enables the effective use of the    

knowledge existing within the company and the professional development of the employees involved (Greco et al., 2013b). The choice of this case enabled the study of the evolution of KM and the analysis of its participation and measurement of social media. In Eni, KM activities have evolved over time. In the late 90s the inclusion of KM as an organization’s best practice ensured that collaboration would be institutionalized and that knowledge sharing would occur. Knowledge transfer started to be referred to as the most important and challenging knowledge activity due to the high complexity it possessed. From then onwards Eni started to pursue a dual objective with regard to KM: that of systematising the explicit knowledge present and widespread within their organisations in order to facilitate its more effective re-use; and that to elicit the tacit knowledge of employees so as to ensure that KM would become a shareable asset within the company. Further objectives of the KM program in Eni have been both to capture individual experience and transform it into established company assets, and to increase interactions among the different professional groups. Professionals were considered to be the crucial success factor of this strategy, and the KM system was built around those employees and their behaviour. However, it was clear that the implementation of such a strategy would soon have needed a supporting structure to facilitate the development of the KM system (Scarso et al., 2009). The first KM initiatives were based on the development of Communities of Practice, the use of collaboration tools and portals and, with the aim of creating a system, relied on the integration with professional models and management and development processes. The Communities of Practice (CoP) gave participants the opportunity to share their knowledge and experience on a particular topic, subject or process of their own interest and in support of their organisation. In 2011 Eni’s KM system included 58 active CoPs, with a 9% increase from the previous year (figure 1).

Figure 1: Eni CoPs    

The members of the CoPs have risen from 2,624 to 3,634, an overall increase of 38% (figure 2). Breaking down this increase into its component parts showed that foreign operations alone accounted for 47% of the total.

Figure 2: Eni CoP members

With the aim of supporting and enhancing expertise and strategic know-how, Eni introduced the figure of Knowledge Owner (KO) into its professional system, responsible for the company’s knowledge in one specific topic area and whose know-how was characterised by a long-standing experience rarely available in the labour market. To date there are 187 KOs in Eni, including 89% with a seniority of more than 15 years. In 2011, investment in the training of a dedicated faculty of internal, qualified and certified professional trainers continued for some specific business and cross-sector areas and involved approximately 200 employees, between knowledge-owners and resources deemed able to pass on their work and professional experience by training young employees, with the view of creating a greater partnership between different generations. KM theory is evolving towards an approach that is even more based on employees and tools ready to handle more challenging KM applications. The last information technology innovations, such as social media, have revolutionised the employees’ approach to collaboration and knowledge sharing. Eni was aware of these changes and a social network was created to better follow the user’s needs and to improve knowledge sharing and collaboration. Social media were implemented with the specific aim of reducing the project cycle time and improving the company’s performance. Hence, social technologies were designed to make the most of such experience and, in particular, to allow the exploitation of the full potential of each employee in the different productive areas.    

As a beta version of an experimental project, Eni applied the first social media to the Corporate ICT area and, specifically, to a target of about 600 employees. This project originated in 2009 from a brainstorming session of a group of employees in the ICT area based in Italy, as an experiment to exploit new technology potentialities in supporting KM. On that occasion, the analysis of the current situation, the employee participation, and some considerations regarding the technological offer of the external landscape all led to the devising of a project aimed also at offering services to highlight some aspects that were sometimes not emphasized enough in the traditional KM approach. The resulting framework was applied to understand the real needs and trends of employees and the gap present with respect to the existing technological scenario. The main aspect that emerged was the need to place employees at the centre of the approach. In particular, the most perceived requirements suggested that real competencies and leadership had to exist and that a knowledge map should be provided. Moreover, many other needs were recognized, such as the need for a flexible but efficient environment, able to support the constantly changing business requirements as a result of an even more complex background. Even though the internal technological landscape was well equipped, the rapidly evolving external environment highlighted new tendencies. Employees started to become accustomed to dealing with new technologies, such as Web 2.0, and aware of the fact that their approach to collaboration, interactive information sharing and interoperability was changing worldwide. So, there was evidence of a gap emerging between the rigidity of the strict organizational rules and procedures and the external easy and flexible world. For this reason the ICT employees decided to break from the traditional KM approach by adopting new technological solutions tailored to the employee needs (Alberghini et al, 2013). A modular social network was created to introduce a new working environment, in which employees were invited to personalize their own profiles, share documents and write their own blogs. Moreover employees were also incentivized to post their ideas to improve the    

ICTs’ working life and processes in a specific area of the company’s social network, called Working Room. Once the tool had been delivered, questions arose regarding how the individual involvement could be analysed and how the factors that influenced the employee participation could be investigated. Hence, it was necessary to define a tailor-made way to monitor the diffusion, the individual participation and the involvement of social media and to measure their impact on KM. Eni decided to select the appropriate factors which could account for the increase in individual participation in social media. Since the process of selecting the appropriate KPIs was very important, the Eni staff, supported by university researchers, decided to define and apply an innovative methodology. The definition and application of this methodology, described in the following sections, were conducted with the direct involvement of the Eni staff and the support of university researchers.

5. The definition and the application of the methodology The methodology is structured in four main steps: the definition of the strategic objectives, the rationalization process, the application and monitoring of measurement and, finally, the proposal of corrective actions (Figure 3). This methodology is essentially based on a PDCA (plan–do–check–act) iterative four-step management method, used mainly in business for the control and continuous improvement of processes and products (Deming, 1986). The first step defines the strategic objectives. Success of KM strongly depends on the selection of initiatives that align with organizational strategy (Rasmus, 2002). Once the strategic purposes have been delineated, the second step deals with the rationalization of the KPI through the correct innovation of web social metrics. This point derives directly from experience which suggests that the best way to monitor a social network is achieved by learning about how the web works. In the third step, the application and the monitoring of the social network through the selected KPIs are shown. The last step concerns the corrective actions to be applied to all    

the information. The process described is cyclic in that changes occurring over time could induce a new definition of strategic objectives and a review of all the steps. The following sections describe the application of each step of the methodology in detail.

Figure 3: The methodology steps

5.1 Definition of strategic objectives In this first step of the methodology the strategic purposes were identified. During this process several issues considered to be particularly relevant by Eni were taken into consideration: the fundamental role of KM in improving organizational and business processes; the relevance of social technologies for sharing, cultivating and circulating knowhow; the need for having a structured access to the information and documentation and to all the links dealing with knowledge at its disposal. Therefore the main aim of the specific case study was identified as the improvement of user engagement by using the company’s social network. To incentivize participation employees were invited to post their ideas so as to improve ICT’s organization and working life. Every idea could be voted and commented on. At the same time, another aim of the project was established: finding the correct KPIs able to measure the company’s social network utilization and the degree of the users’ participation and involvement. Three main phases were identified to meet the previous purposes of incentivizing participation and of choosing the correct KPIs: the promotion of collaboration, the support of know-how diffusion and the fostering of the key node emergence (Figure 4).

Figure 4: KM Strategic Purposes

   

Promoting collaboration means that a continuous effort should be made to support information sharing and to increase the number of employees who collaborate and share documents and knowledge. Moreover, this phase considers involving and highlighting the dialogues on published content by offering interaction and collaboration tools. Supporting know-how diffusion aims to stimulate the search and the consultation of shared content, and facilitate information diffusion and data accessibility. Finally, letting the key nodes emerge means letting competence centres emerge through strategic figures, beyond hierarchies, and to monitor the authority of content.

5.2 Rationalization In the second step of the methodology KPIs which could allow the monitoring of employee involvement and of the increase in their participation were selected. For the analysis of employee involvement, it was decided to use the three main social media and web innovation metrics (Fisher, 2009; Guarda, 2009; Hanna et al., 2011). The first one is the Return on Attention (RoA), a metric that refers to the benefits (and costs) received in return for the time spent to complete an activity. It is well known that in a world which is becoming ever more digitalized, attention is starting to become an important factor. In detail, the RoA metric includes the number of participants over a period of time, the number of relationships, the audience, the average time spent on the site and the access frequency. The second metric is the Return on Information (RoI), which is based upon the value of relevant data returned through search. In detail, the RoI metric is represented by the frequency with which users receive newsletters and periodic communications. The third metric is the Return on Skills (RoS), which measures the value of considerable capabilities returned. Social communities are able to attract users with high skills and build a knowledge map. In detail, the RoS metric includes specific actions carried out by participants, such as the

   

personalization of their own profiles (personal photos and background, mood change, the followers’ activities and blogs). For the increase in user participation, it was decided to analyse the possibility of offering a useful job tool which could intercept the daily user flow. In this regard, several key types of metric can be tracked, such as traffic data, follower data, social interaction and social content performance. From the social media and web innovation metrics described above, a set of clear and meaningful KPIs was selected to measure social media within Eni and to analyse the degree of participation and involvement of its users. In Figure 5 the selected KPIs are presented and grouped following their adherence to each category. In particular, participation is focused on users and access frequency, attention is focused on contribution quantity and interaction, and relationship is focused on network size. A particular function was added to analyse and filter the KPIs by using variables, such as time (the selected period), rooms (the selected working room), idea categories, and ideas posted by users.

Figure 5: the selected indicators

5.3 Application and monitoring In the third step of the methodology, the defined and rationalized KPIs were applied and monitored. In order to facilitate and better verify the operability of the application of the KPIs, a modular tool was created by using open source technologies. This tool allowed the introduction of a new working environment and the monitoring of employee needs and their constant changes. Each module of the tool was made ready to implement a service that could be added to personalize profiles. The addition of this modular tool to the Eni social media environment    

favoured the possibility to scale large groups and to improve their integration. By using the above-mentioned tool, employees were invited to post their ideas to improve ICT’s processes and working life in a dedicated area, called Working Room. A pilot working room was created first and its operability was tested. After this first step all the users were allowed to create other working rooms. To measure the users’ involvement, all data was collected daily and analysed by a specific monitoring tool. This tool was a business intelligence software, which combined the features of dynamic presentations, instantaneous data manipulation, and real-time data analysis. With this software, end-users (allowed to see the dashboard) were given presentations on an interactive software program that allowed them to enter new data or simply move saved data around so that they could see the same set of data from different viewpoints on the same presentation. Moreover, a dedicated summary dashboard was created for top managers to report the main aspects of their involvement. The monitoring software created real-time customized presentations by allowing end-users to quickly move and change data.

5.4 Corrective Actions The input experimentally received from the users of the beta version of the social media, as obtained during the application and monitoring step, provided the corrective actions which constitute the last step of the methodology. A daily analysis of the results of the selected KPIs helps to understand real user involvement and trends. To better address the users’ needs and to encourage their participation it was necessary to make some changes to both the analysis and the modular tool. Since employees had been invited to post their ideas to improve ICT’s organization and working life, many employees started to express their opinion. A constant monitoring made many aspects of the employee involvement emerge and also gave the cue to add some new KPIs and change some existent ones. This is because some degree of uncertainty had arisen during the operation of    

the initial starting set of KPIs. For example, in this project, it had been planned that, after a first monitoring phase, it would have been useful to add historical data to measure the trend with respect to a particular period, so the time variable had been enhanced in order to have a general overview of the whole report situation regarding the users’ involvement and participation. Furthermore, as changes in circumstances may have revealed new information and brought in new employees with new ideas, it had been decided that KPIs should always adapt to every new eventuality. The tool’s flexibility represents a strong point in the workability of the application due to the fact that, because of its cyclic nature, new contributions from users can produce the addition of a new phase, or have doubts about the chosen strategy of operations, or the variables themselves, as well as the KPIs.

6. Findings of the application of the methodology and research results The results derived from the application of the proposed methodology to the Corporate ICT area of Eni are summarized in Figure 6. The results of the application account for the number values of participation, attention, and relationship indicators.

Figure 6: Results of the application of the KPIs

For individual participation the results show that in the emerging social technology users were considerably attracted by the social network presented (95% of employees involved) and most of them (70%) proved to be active users, namely those who actively accessed the site in a specific period or have at least browsed the site. The average number of visits per week showed a good participation, comparable to that of other similar common internet social networks, thus proving that users quickly started to consider this tool useful. On the grounds of the tool’s flexibility and of the possibility of intervening to interactively make use of external contributions, it was decided to leverage its usefulness, ease of use, and    

attraction to increase individual participation. In this case usefulness was obtained mainly from the working rooms, virtual spaces that help employees collaborate in an easy and pleasant way. The number of working rooms increased day by day. To confirm the viral diffusion of this tool, a high level of initial participation, consisting of subscription, profile personalization and relationship creation, was registered (99% of employees involved). As pointed out above, some corrective actions were adopted right away in the ICT area of Eni to improve the involvement of employees and encourage participation. For example, it must be pointed out that employees might worry about posting ideas in contrast with those expressed by their superior managers. Also, it was noted that after three comments, employees started to feel comfortable with displaying their comments and the discussion could start. Moreover, the participation increase was also achieved thanks to a moderator who began sending messages through newsletters and new posts on the site to encourage new comments. In this way, employees convinced themselves to use the social media tool and to submit their proposals and ideas. Moreover, it emerged that the role of social influence could be better analysed through the effects of the reciprocal swaying on each contribution. A high level of participation was registered by the growing trends in adding ideas, documents, comments and votes. These trends appeared to be related to the trust and familiarity with the environment and to the encouragement given by the moderator. The same motivation was also key to the average number of visits per week. In particular, for the first pilot working room, there was a very satisfactory response. Every idea posted received a considerable number of comments (average number of 5,4 with a maximum of 25) and votes (average number of 12,1 with a maximum of 33). It is important to note that this viral diffusion was completely autonomous since the employees were not aware of the future development or strategy of the pilot project. The user base proved to be very observant and it was crucial to apply a continuous and active monitoring to always keep the company’s social network alive.

   

Figure 7 presents the trend of the ideas, comments and votes posted during the first month, while figure 8 shows the involvement and participation of users (in particular the 20 users who gave the highest number of contributions in the same period).

Figure 7: Ideas, comments and votes of the first month trend

The choice of the correct KPIs proved to be critical in monitoring the user needs and trends and make the right decisions in order to increase knowledge sharing and participation by encouraging actions that would provide better collaboration. Of course, it was necessary to take the degree of uncertainty into account. It must be underlined how new events might require a revision of the KM strategy which could lead to searching for new KPIs. Therefore data under analysis can change frequently and a constant monitoring can be useful to analyse any new KPIs to be applied.

Figure 8: Ideas, comments and votes per user (first 20 contributors)

The most important result of this project was the start of six new projects, sprung up from the selection and the merging of the best ideas posted in the first pilot working room. All the ideas were analysed and evaluated by a steering committee. Employees who posted ideas were invited to become team leaders (with a maximum of two team leaders) of their project and each team leader could invite a maximum of eight other employees to form their own team. Even though results refer to a limited period of time, they adopted the forward strategy to diffuse the same tool to other areas. The analysis of the results of the application of the methodology to Eni’s social media shows that the four research questions have been answered. With regard to the first question, the    

results of this research demonstrated that individual participation and involvement can be analysed by monitoring a few variables, easily measured, such as the number of the users’ accesses and their frequency. In order to do this, it is particularly important to select the appropriate reference variables able to monitor these aspects. Indeed, the case study has shown strong evidence that the best solution is represented by the customization of the variables on the basis of the typology of the social media and of the operational purposes. Secondly, the research confirmed that, as literature suggests, the most common factors (variables) in terms of attention, information and skills proved to be able to monitor and increase individual participation. With regard to the third question the research results suggest constructing those KPIs which can help organizations incentivize user engagement by relying on the known web metrics (RoA, RoI, and RoS). The results also showed that the definition of the most precise measurements possible, such as usefulness, ease of use, and appeal, undoubtedly help increase individual participation. It is also worth pointing out that user engagement and individual participation cannot be increased by using only standard tools and procedures and are increased even less by adopting generalized forms of measurement. This study shows that additional solutions can be adopted effectively to increase individual participation, such as: performing flexible or field-dependent evaluations, convincing users about the advantages of social media, providing a moderator; promoting the growth of network relationships. Finally, the answer to the last research question was given by analysing the entities which express the activities regarding knowledge generation and creation, knowledge sharing and transfer, knowledge application and refinement. The proposed entities consist of the number of contributions and interactions, expressed by ideas, comments and votes. By measuring the values of such entities and analysing their trend it was possible to evaluate the KM activities’ performance. Measuring the number of ideas and suggestions allowed the evaluation of the

   

process of knowledge generation, while measuring the number of votes and comments helped evaluate the process of knowledge sharing.

7. Conclusions In this paper we presented a case study approach to define and apply a methodology aiming to measure the employees’ involvement and participation through a company’s social network. The increasing importance of social technologies has prompted organizations to develop a better understanding of their effects in order to seize the most favourable benefits. Furthermore, such benefits have also been considered as capable of influencing the activities regarding KM. The proposed methodology attempts to measure social media’s diffusion, employee participation, and the level of their impact on KM. The methodology consists of four steps and is based on the definition of the high level meta metrics and on the selection of specific KPIs. The innovative feature of this paper lies in the application of the proposed methodology to an unusual field of study, such as an important integrated and multinational company. The approach used took advantage of the uniqueness of the specific case study and of the new themes offered by the emergence of social media in the related theory. The first results were achieved through the application of the methodology to a social media tool, which, in the form of a pilot project, managed to increase individual participation through its usefulness, usability, appeal and trust. Moreover, a high level of cooperation among Eni employees helped capture critical information, designing an implicit knowledge real-time map and applying a qualitative and dynamic analysis of the employee participation trends. In addition, knowledge activities were fostered by constant exchange of skills in a process of openness, trust and innovation. The enthusiastic reaction of the employees also allowed the adoption of a few innovative processes deriving from the selection of the best employee contributions.    

The next step of the project will be the delivery of this tool to the other Business Units, starting with the Exploration and Production unit with a bigger sample of 5000 users. The range of the extension will imply a new communication plan and a deeper analysis to cover different attitudes and needs. Through the definition and the application of the methodology, answers to the research questions were provided. More specifically, this paper shows how the individual participation and involvement of social media users can be measured by a monitoring system tool, which accounts for modalities of utilizations, such as number of accesses and frequency. Moreover, the research also highlighted how the methodology’s flexibility is an essential feature in that other entities are necessary to reinforce the user’s engagement in social media in addition to the most common factors (variables) regarding attention, information and skills and the connected web metrics, such as RoA, RoI, and RoS. Indeed, the methodology showed that a correct choice of suitable KPIs is critical in monitoring the user’s needs and trends and to make the right decisions regarding the increase of knowledge sharing and participation among employees. It is a fact that KPIs have maximum efficiency only if they are flexible enough to adapt to the frequently changing situations. Finally, the results of this paper show how the performance of the KM activities, such as knowledge generation and sharing, can be measured and analysed by monitoring the number of new ideas and suggestions and by evaluating votes and comments provided by users. In conclusion the methodology proves to be capable of monitoring the collaboration and knowledge sharing activities among employees and to incentivize the participation and involvement of employees who make use of the company’s social media. The possibility of constantly modifying the adopted social media tool by means of corrective actions together with the possibility of adapting the KPIs to new situations make the present methodology an efficient management approach to take on the multifaceted activities of a social media environment.    

The paper is based on the application of the described approach to the Corporate ICT area of a single, and large, company, which limits the possibility of making general conclusions. The representative nature of the survey group, together with the data collection methods employed, were the key strengths of the study’s approach. However, there is a key limitation regarding the survey group due to the participation of only a representative sample of people. In spite of the limitations of the proposed application, it is expected that from this research more in-depth explorations could initiate toward different environments of management application, namely, the application of this methodology to all the Business Units of a Company.

8. References Alavi, M., Leidner, D., 1999. Knowledge management systems: Issues, challenges, and benefits. Communications of the Association for Information Systems, 1(2; Art. 1), 1–37. Alavi, M., Leidner, D.E., 2001. Review: knowledge management and knowledge management systems: conceptual foundations and research issues, MIS Quarterly, 25, 107–136. Alberghini E., Cricelli L., Grimaldi M., 2010, Implementing knowledge management through IT opportunities: definition of a theoretical model based on tools and processes classification, ECIC 2010: The Proceedings of the 2nd European Conference on Intellectual Capital, Lisbon, Portugal, 29-30 March, 2010, pp. 22-33. Alberghini, E., Cricelli, L. and Grimaldi, M., 2013. KM versus enterprise 2.0: a framework to tame the clash, Int. J. Information Technology and Management, 12 (3/4), 320–336. Awazu, Y., Desouza, K., 2004. Open knowledge management: Lessons from the open source revolution, Journal of the American Society for Information Science and Technology, 55(11), 1016–1019. Bailey, K., Francis, M., 2008. Managing information flows for improved value chain performance, International Journal of Production Economics, 111(1), 2-12.

   

Baird, C.H., Parasnis, G., 2011. From social media to social customer relationship management, Strategy & Leadership, 39(5), 30-37. Barchiesi, M.A., Costa, R. and Greco, M. 2014. Enhancing conflict resolution through an AHP-based methodology, Int. J. Management and Decision Making,13(1), 17–41. Barclay, C. Osei-Bryson, K.M., 2010. Project performance development framework: An approach for developing performance criteria & measures for information systems (IS) projects, International Journal of Production Economics, 124(1), 272-292. Bebensee, T., Helms, R., Spruit, M., 2011. Exploring Web 2.0 applications as a means of bolstering up knowledge management, Electronic Journal of Knowledge Management, 9, 1–9. Billington, M.G., Billington, P. J., 2012. Social Media Tools for Leaders and Managers, Journal of Leadership, Accountability and Ethics, 9(6), 11-19. Bloodgood, J.M., Salisbury, W.D., 2001. Understanding the influence of organizational change strategies on information technology and knowledge management strategies, Decision Support Systems, 31, 55–69. Borgatti, S. P., Foster, P. C., 2003. The network paradigm in organizational research: A review and typology. Journal of management, 29(6), 991. Bowman, N.D., Westerman, D.K., Claus C.J., 2012. How demanding is social media: Understanding social media diets as a function of perceived costs and benefits – A rational actor perspective, Computers in Human Behavior, 28, 2298–2305. Brass, D. J., 2009. A social network perspective on industrial/organizational psychology. The Oxford Handbook of Organizational Psychology. New York: Oxford University press Brogi, S., Calabrese, A., Campisi, D., Capece, G., Costa, R., Di Pillo, F., 2013. Effects of online brand communities on brand equity in luxury fashion industry, International Journal of Engineering Business Management, 5(Spl. Issue), 1-9. Bruque, S., Moyano, J., Eisenberg, J., 2008. Individual adaptation to IT-induced change: The role of social networks, Journal of Management Information Systems, 25, 177–206. Butler, B.S., 2001 Membership size, community activity, and sustainability: A resource-based model of online social structures. Information Systems Research, 12:4, 346–362.    

Calabrese, A. 2012. Service productivity and service quality: A necessary trade-off?. International Journal of Production Economics, 135(2), 800-812. Calabrese A., Campisi. D., Capece G., Costa R., Di Pillo F. 2013. Competiveness and innovation in high-tech companies: an application to the Italian biotech and aerospace industries, International Journal of Engineering Business Management, 5(1), 1-11. Chang, W.L., Yuan, S.T., Li, E.Y., 2009. iCare home portal: An extended model of quality aging eservices, Communications of the ACM, 52, 118–124. Cheung C.M.K., Lee M.K.O., 2010. A theoretical model of intentional social action in online social networks 2011 Decision Support Systems, 49, 24–30. Cho, H., Chen, M. H., Chung, S. 2010. Testing an integrative theoretical model of knowledge sharing behavior in the context of Wikipedia. Journal of the American Society for Information Science and Technology, 61(6), 1198–1212. Choong, K.K., 2008, "Intellectual capital: definitions, categorization and reporting models", Journal of Intellectual Capital, 9(4), 609 – 638. Christensen, C.M., Marx, M., Stevenson, H.H., 2006. The tools of cooperation and change, Harvard Business Review, October: 73-80. Christensen, C.M., Wang D., van Bever, D., 2013. Consulting on the cusp of disruption. Harvard Business Review, October, 106-115. Chung K.S.K., Hossain L., 2009. Measuring Performance of Knowledge-Intensive Workgroups Through Social Networks, Project Management Journal, 40(2), 34–58. Chung, S., Byrd, A., Lewis, B., Ford. F. 2005. An empirical study of the relationships between IT infrastructure, flexibility, mass customization, and business performance. The Database for Advances in Information Systems, 36(3), 26–44. Constantinides, E., Fountain, S., 2008. Web 2.0: Conceptual foundations and marketing issues, Journal of Direct, Data, and Digital Marketing Practice, 9, 231–244. Corvello, V., Migliarese, P. 2007. Virtual forms for the organization of production: A comparative analysis. International Journal of Production Economics, 110(1), 5-15.

   

Cricelli, L., Grimaldi, M., 2008. A dynamic view of knowledge and information: a stock and flow based methodology, International Journal of Management and Decision Making, 9(6), 686-698. Cricelli, L., Grimaldi, M., 2010. Knowledge-based Inter-Organizational Collaborations, Journal of Knowledge Management, 14(3), 348-358. Culnan, M., McHugh, P., Zubillaga, J., 2010. How large U.S. companies can use twitter and other social media to gain business value. MIS Quarterly Executive, 9(4), 243–259. Dabner, N., 2012. ‘Breaking Ground’in the use of social media: A case study of a university earthquake response to inform educational design with Facebook, The Internet and Higher Education, 15(1), 69-78. Davenport T.H., Beck J.C., 2000. Getting the Attention You Need. Harvard Business Review, September –October, 119-126. De Felice, F., Petrillo, A., 2012. Methodological Approach for Performing Human Reliability and Error Analysis in Railway Transportation System. International Journal of Engineering and Technology, 3(5), 341-353. De Felice, F., Petrillo, A. (2013). Decision-Making Analysis to Improve Public Participation in Strategic Energy Production Management. In Multicriteria and Multiagent Decision Making with Applications to Economics and Social Sciences (pp. 129-142), Springer, Berlin Heidelberg. Deming, W.E., 1986. Out of the Crisis, MIT Center for Advanced Engineering Study, MIT Press, Cambridge, MA. Di Gangi, P. M., Wasko, M., 2009. Steal my idea! Organizational adoption of user innovations from a user innovation community: A case study of Dell IdeaStorm. Decision Support Systems, 48(1), 303-312. Di Gangi, P. M., Wasko, M., Hooker, R.E., 2010. Getting customers’ ideas to work for you: Learning from Dell how to succeed with online user innovation communities. MIS Quarterly Executive, 9(4), 163–178. Durugbo, C., 2012. Modelling user participation in organisations as networks, Expert Systems with Applications, 39(10), 9230-9245.

   

Eisenhardt, K.M., 1989. Building Theories from Case Study Research, Academic Management Review, 14(4), 532-550. Falcone, D., Silvestri, A., Di Bona, G., Forcina, A., Pacitto, A., 2010. Study and Modeling of Lines at High Flexibility through Simulation, Proceedings of EAIA (Emerging Applications in Industry and Academia), Orlando (USA), 11-15 April 2010. Falcone, D., Forcina, A., Di Bona, G., Duraccio, V., Silvestri, A., Cerbaso, C., 2013. Technical and economic verification of the convenience in reengineering a production line using simulation techniques. In: the 25th European Modeling and Simulation Symposium, EMSS 2013 , pp. 327332. Falsini, D., Fondi, F., Schiraldi, M. M. 2012. A logistics provider evaluation and selection methodology based on AHP, DEA and linear programming integration. International Journal of Production Research, 50(17), 4822-4829. Faraj, S., Jarvenpaa, S.L., Majchrzak, A. 2011. Knowledge collaboration in online communities, Organization Science, 22, 1224–1239. Ferron M., Massa P., Odella F. 2011. Analyzing collaborative networks emerging in Enterprise 2.0: the Taolin Platform Procedia, Social and Behavioral Sciences, 10,68–78. Fisher, T. 2009. ROI in social media: A look at the arguments, Journal of Database Marketing & Customer Strategy Management, 16(3), 189-195. Frantz, C., Mayer, F.S., Norton, C. and Rock, M. 2005. There is no "I" in nature: The influence of self-awareness on connectedness to nature, Journal of Environmental Psychology, 25(4), 427-436. Goodhue, D.L., Thompson, R.L., 1995. Task-technology fit and individual performance, MIS Quarterly, 19(2), 213–236. Gopal, R., Marsden, J.R., Vanthienen, J. 2011. Information mining — reflections on recent advancements and the road ahead in data, text, and media mining. Decision Support Systems, 51(4), 727–731. Goswami, A., Bharathi, S.V., Raman, R., Kulkarni, A., Joseph, S., Kelkar, B. 2013. Synergies between Social Media Features and User Engagement to Enhance Online Brand Visibility - A Conceptual Model, International Journal of Engineering and Technology, 5(3), 2705-2718.    

Grant, R., 2007. Contemporary Strategy Analysis: Concepts, Techniques, Applications, 6th Edition, Blackwell Publishing, Oxford. Greco, M., Baldissin, N., Nonino, F. 2013a. An Exploratory Taxonomy of Business Games. Simulation & Gaming, 44(5), 645-682 Greco, M., Cricelli, L., Grimaldi, M., 2013b. A strategic management framework of tangible and intangible assets, European Management Journal, 31 (1) , pp. 55-66. Green, A., Ryan, J.C.H., 2005. A framework of intangible valuation areas (FIVA): Aligning business strategy and intangible assets, Journal of Intellectual Capital, 6(1), 43–52. Grimaldi, M. Cricelli, L. Rogo, F., 2013. A theoretical framework for assessing managing and indexing the intellectual capital, Journal of Intellectual Capital, 14(4), 501-521. Guarda, D., 2009. Social Media and Web Innovation metrics: ROA Return on Attention & ROI Return on Investment http://www.dinisguarda.com/social-media-and-web-innovation-metrics-roareturn-on-attention-roi-return-on-investment/ Haefliger, S., Monteiro, E., Foray, D., von Krogh, G., 2011. Social software and strategy, Long Range Planning, 44, 297–316. Hanna, R., Rohm, A., Crittenden, V.L. 2011. We’re all connected: The power of the social media ecosystem, Business Horizons, 54(3), 265-273. Hansen, D., Shneiderman, B., Smith, M.A., 2010. Analyzing Social Media Networks with NodeXL: Insights from a Connected World; Morgan Kaufmann. Print ISBN-13: 978-0-12-382229-1. Hansen, M.T., Nohria, N., 2004. How to build collaborative advantage. MIT Sloan Management Review, 46 (1), 22-30. Hendler, J., Golbeck, J., 2008. Metcalfe’s law, web 2.0 and the semantic web. Web Semantics: Science, Services and Agents on the World Wide Web, 6(1), 14–20. Huysman, M., de Wit, D., 2004. Practices of managing knowledge sharing: towards a second wave of knowledge management, Knowledge and Process Management, 11(2), 81–92. Kahai, S.S., Cooper, R.B., 2003. Exploring the core concepts of media richness theory: The impact of cue multiplicity and feedback immediacy on decision quality, Journal of Management Information System, 20(1), 263–299.    

Kaplan, A. M., Haenlein, M. 2010. Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59–68. Kietzmann J.H., Hermkens K., McCarthy I.P., Silvestre B.S. 2011., Social media? Get serious! Understanding the functional building blocks of social media, Business Horizons, 54(3), 241–251. Koo, C., Wati, J., Jung, J.J., 2011. Examination of how social aspects moderate the relationship between task characteristics and usage of social communication technologies (SCTs) in organizations. International Journal of Information Management, 31(5), 445-459. Koskinen, M., Luomala, J., & Maaranen, P. 2012. Ict-related Intangibles And Organizational Innovation: Indicators For Improving Connectedness And Flexibility. Human Technology: An Interdisciplinary Journal on Humans in ICT Environments, 8(1), 24-45. Langley, D., van den Broek, T. 2010. Exploring social media as a driver of sustainable behaviour: case analysis and policy implications. In: Internet Politics and Policy Conference 2010, 16‐17 September, Oxford, UK. Lee, C.S., Ma, L., 2011. News sharing in social media: The effect of gratifications and prior experience, Computers in Human Behavior, 28, 331–339. Levy, M., 2009. ‘Web 2.0 implications on knowledge management’, Journal of Knowledge Management, 13(1), 120-34. Levy, M., 2013. Stairways to heaven: implementing social media in organizations, Journal of Knowledge Management, 17(5), 741 – 754. Li, C., Bernoff, J., 2008. Groundswell: Winning in a World Transformed by Social Technologies. Harvard Business Press, 2(1), 181-183. Lin, W.B., 2006. The exploration of employee involvement model, Expert Systems with Applications, 31(1), 69-82. Mancini, V., Pasquali, M., Schiraldi, M.M., 2012. Opportunities for using RFID in the aircraft production process, International Journal of RF Technologies: Research and Applications, 3(4) , 243-255. Mangold, W. G., Faulds, D. J., 2009. Social media: The new hybrid element of the promotion mix original, Business Horizons, 52(4), 357–365.    

Marra, M., Ho, W., Edwards, J.S., 2012. Supply chain knowledge management: A literature review. Expert Systems with Applications, 39(5), 6103-6110. McAfee A. P., 2006. Enterprise 2.0: The Dawn of Emergent Collaboration, MIT Sloan Management Review, 47(3), 20-28. Moeller, K., 2009. Intangible and financial performance: causes and effects, Journal of Intellectual Capital, 10(2), 224-245. Molina, L.M., Lloréns-Montes, J., Ruiz-Moreno, A., 2007. Relationship between quality management practices and knowledge transfer, Journal of Operations Management, 25(3), 682-701. Newell, S., Robertson, M., Scarbrough, H., Swan, J., 2002. Managing Knowledge Work. Palgrave MacMillan, London. Nonaka, I., Takeuchi, H., 1995. The Knowledge Creating Company. Oxford: Oxford University Press. Nov, O., Naaman, M., Ye, C. 2010. Analysis of participation in an online photo sharing community: A multidimensional perspective. Journal of the American Society for Information Science and Technology, 61(3), 555–566. Oliver, M.B., Raney, A., 2011. Entertainment as pleasurable and meaningful, Journal of Communication, 61, 984–1004. Orlikowski W. 1996. Evolving with notes, organizational change around groupware technology. In Groupware and Teamwork, Ciborra CU (ed.). Wiley: Chichester; 23–60. Pantano, E., Corvello, V., 2013. The impact of experience on companies' reactions to negative comments on social networks. Journal of Direct, Data and Digital Marketing Practice, 14(3), 214223. Paroutis, S., Al Saleh, A., 2009. Determinants of knowledge sharing using Web 2.0 technologies, Journal of Knowledge Management, 13, 52–63. Patel, H., Pettitt, M., Wilson, J.R., 2012. Factors of collaborative working: A framework for a collaboration model. Applied Ergonomics, 43(1), 1-26. Pavlou, P.A., 2005. Measuring the Return on Information Technology: A Knowledge-Based Approach for Revenue Allocation at the Process and Firm Level. Journal of the Association for Information Systems, 6(7), 199-226.    

Picazo-Vela, S., Gutiérrez-Martínez, I., Luna-Reyes, L.F., 2012. Understanding risks, benefits, and strategic alternatives of social media applications in the public sector, Government Information Quarterly, 29, 504–511. Quan-Haase, A., Young, A.L., 2010. Uses and gratifications of social media: A comparison of Facebook and Instant Messaging. Bulletin of Science, Technology & Society, 30, 350–361. Rasmus, D.W., 2002. Targeting Knowledge Management Initiatives - Planning Assumption. Forrester Research, Cambridge, MA. Razmerita, L., Kirchner, K. and Sudzina, F., 2009. Personal knowledge management: the role of Web 2.0 tools for managing knowledge at individual and organizational levels, Online Information Review, 33(6), 1021-39. Rice, R.E., Bair, J.H., 1984. New organizational media and productivity. In R. E. Rice (Ed.), The new media: Communication, research, and technology (pp. 185–216). New-bury Park, CA: Sage Publications. Scarso, E., Bolisani, E., Salvador, L., 2009. A systematic framework for analysing the critical success factors of communities of practice, Journal of Knowledge Management, 13(6), 431-447. Schaik, P. van, Ling, J., 2008. Modelling user experience with web sites: Usability, hedonic value, beauty and goodness, Interacting with Computers, 20(3), 419-432. Seo, D., La Paz, A., 2008. Exploring the dark side of IS in achieving organizational agility. Communications of the ACM, 51(11), 136–139. Sinclaire, J.K., Vogus, C.E., 2011. Adoption of social networking sites: an exploratory adaptive structuration perspective for global organizations, Information Technology and Management, 12(4), 293-314. Sinderen, M. V., Almeida, J.P.A., 2011. Empowering enterprises through next generation enterprise computing. Enterprise Information Systems, 5(1), 1–8. Tailor, D., 2008. Does social media really connect you to humanity? Forum Newsletter, 18–21. von Krogh, G., 2012. How does social software change knowledge management? Toward a strategic research agenda, The Journal of Strategic Information Systems, 21 (2), 154-164.

   

Vuori V., Okkonen, J., 2012. Knowledge sharing motivational factors of using an intra-organizational social media platform, Journal of Knowledge Management, 16(4), 592 – 603. Wilson, J., 2009. Social networking: The business case, Engineering and Technology, 4(10), 54–56. Yang, J., 2010. The knowledge management strategy and its effect on firm performance: A contingency analysis, International Journal of Production Economics, 125, 215–223. Yates, D., Paquette, S., 2011. Emergency knowledge management and social media technologies: A case study of the 2010 Haitian earthquake, International Journal of Information Management, 31(1), 6-13. Zenk, L., Stadtfeld, C., Windhager, F., 2010. How to analyze dynamic network patterns of high performing teams, Procedia Social and Behavioral Sciences, 2, 6418-6422.