CHAPTER IINTRODUCTIONGeneral BackgroundTraditionally

March 8, 2019 Critical Thinking

CHAPTER IINTRODUCTIONGeneral BackgroundTraditionally, agricultural information exchange has been dominated by industrial media such as newspapers, television, and magazines. In recent years, however, technology awareness and computer literacy are increasing across all demographics and various forms of social media are being used more and more by people looking for news, education, and other information including agriculture, health and so on. Social media can be defined as internet-based applications that allow the creation and exchange of user-generated content. It is the blending of technology and social interaction that creates value in these types of media. Social media and other mobile platforms enable individuals to post messages along with specific geographic information (Cassa, et al., 2013). These messages can help track infectious disease outbreaks (Chunara, et al., 2012) aid in natural disaster response (Lu, et al., 2012) and provide insight into conflicts (Heinzelman, et al., 2011), where data collected through official reporting structures can take weeks to collect and analyze.
Major agricultural extension methods are grouped into the three forms of individual, group and mass media. Social media majorly fall into the mass media methods of communicating agricultural messages. In most literature, Social media is used interchangeably with the emergence of Information, Communication and Technology use in agricultural extension and advisory services though Social media is a wide term. As, ICTs have revolutionized the processes of transferring of agricultural knowledge or innovation that are designed to boost agricultural production. So, Social media as part of ICTs will have the same effect on the increasing the efficacy of the agricultural extension workers’.
Social media sites (e.g., Flickr, YouTube, Twitter and Specially Facebook) are a popular distribution outlet for users looking to share their personal news and interests. As a result, these sites host substantial amounts of user-contributed materials (e.g., photographs, videos, and textual content) for a wide variety of real-world events, ranging from popular, widely known events to smaller events that might receive no coverage in traditional news outlets. By identifying all these events and their associated social media documents we can enable powerful local event browsing and search, to complement and improve the local search tools that Web search engines provide. Food and Agricultural Organization (FAO) reported that in many developing countries, wide adoption of research results by majority of farmers remains quite limited. This therefore, calls for a system which allows adequate information flow from researchers to farmers and vice-versa. Hence, Agricultural extension agencies that use electronic media have a central role in facilitating the flow of a variety of information to offer the needed exposure of farmers to innovation for overall development.

What is social media?
Social media refers to the internet-based digital tools for sharing and discussing information among people. It refers to the user generated information, opinion, video, audio, and multimedia that is shared and discussed over digital networks (Andres and Woodard, 2013). Merriam-Webster (2015) defines social media as forms of electronic communication through which users can create online communities to share information, ideas, personal messages and other content. The definition of Ahlqvist et al. (2008) is focused on three basic components – content, communities and Web 2.0 and operationalizes social media as the interaction of people and also to creating, exchanging and commenting contents in virtual communities and networks. According to Michelle Chmielewski (2011), social media is not about what each one of us does or says, but about what we do or say together, worldwide, to communicate in all directions at any time by any possible digital means. Social media are basically digital technologies facilitating communication of user generated content through constant interaction (Terry, 2009; Kaplan and Haenlein, 2010). In a nut shell, social media are web based tools of electronic communication that allows users to interact, create, share, retrieve, and exchange information and ideas in any form (text, pictures, video, etc.) that can be discussed upon, archived, and used by anyone in virtual communities and networks. Aspects of social media that makes them an important and accessible tool in development communication are their easy access through mobile phones, mass-personal communication and mass-self communication, a larger set of weak ties to ensure receipt of novel ideas, high degree of connectedness, and link ability and content sharing across multiple platforms (Hemsley and Mason, 2013). The types described above are a broad categorization of the existing social media platforms but many a times, it becomes difficult to clearly classify them in a strict category as evolution of social media platforms depending on user’s preference is very common and integration of new features makes them fit in more than one category at times. Social media is more about sociology and psychology of communication than about technology (Saravanan and Bhattacharjee, 2014). Major characteristics of social media that distinguishes this form of online communication from others are participation, openness, conversation, community, and connectedness (Mayfield, 2008). The phenomenal growth of social media can mostly be attributed to the common platform it gives to people to share their ideas and create their own content – be it texts, images, sound clips or videos and also the affordability of these platforms as they can be accessed without incurring extra charges, Convergence of technologies and evolution of multi-functional portable gadgets are other reasons for expanding social media reach. The popularity of these social media platforms to a global audience is like never before owing to the increased reach of internet enabled mobile phones and increased number of social media platforms across the globe. Social media sites gained their popularity not only because they connected friends and family but the huge potential of communication was soon realized and it started finding its use in professional communication. The preferences of social media platforms are still different based on the purpose. While Facebook has the highest reach among all social media platforms, LinkedIn is still the number one choice for professional communication as it is more likely to have a professional, well informed discussion in LinkedIn which is not possible in Facebook or Twitter. It is not a personal social media platform and that is a reason why 26 per cent of Fortune 500’s Chief Executive Officers (CEOs) are in LinkedIn compared to only 7.6 per cent in Facebook (Simonson, 2013). Platforms for researchers and academicians like Research Gate and Academia.edu allow users to post public questions to the community, both networks group users by institution, allowing users to see colleagues and create subdomains, scores members based on content interaction and score of members interacting with the content, thus quantifying the impact of the researcher in his peer community (Ovadia, 2014). In addition, the hashtag revolution has made content search specific and content reach wider on social media.

Why use social media?
The special features of participation, openness, conversation, community and connectedness makes social media a unique user experience (Mayfield, 2008). According to the latest findings of Bangladesh Telecommunication Regulatory Commission (BTRC) and state counter 93.07% Facebook, 4.93% Youtube, 0.85% twitter .0.21% LinkedIn users in Bangladesh are active among the total percent of internet users. All these statistics prove the huge potential that social media can be for extension practitioners.
Social media can be advantageously used in agricultural extension, as discussed below (Savanna et al., 2015):
Highly cost effective
Simultaneously reaches large numbers of personnel
Location and client specific, problem-oriented
User-generated content and discussion among the community members
Easily accessed from mobile phones
Increases internet presence of extension organizations and their client reach
Democratization of information by making it accessible to all
Brings all stakeholders into a single platform
Can measure reach and success by tracking number of visitors, friends, followers, mentions, Facebook ‘likes’, conversation index and number of shares
These potentials make social media a highly relevant and beneficial platform for extension personnel to share their opinion to a community. With the challenges like limited availability of ICTs and internet facilities in rural areas, their suitability to only educated and online clientele, lack of awareness and readiness to accept social media by extension professionals, breach of individual privacy, piracy of the materials and irrelevant information, the success of social media depends on commitment level of extension workers and community members in using social media for extension. (Saravanan et al., 2015). But in spite of these problems, social media are becoming popular among rural people.

Advances in technology have drastically changed agriculture production methods over the decades. Now, new methods of communication are also changing the way the public learns about agriculture and forms opinions about agricultural. “It is important that agriculturists explore different communication options”. “In my opinion, agriculturists have to take advantage of as many tools as possible to convey the message of agriculture,” Hawkins said.

Use of social media generates a new audience. Twitter, Facebook and YouTube allow agricultural workers to tell their stories in their own words. The masses of people who use Facebook and Twitter create new ways to share with otherwise uniformed people. According to Statisticsbrain.com, there are more than 1.2 billion people who use Facebook worldwide. Agricultural workers can share what is important to them and what changes they wish to see in the agriculture industry. Social media captures widespread users. Interesting stories trending on Twitter or Facebook are more likely to be read than buried deep in a newspaper. Facebook is the world’s most popular social networking website as it makes it easy to connect with family and friends and share pictures, websites and videos. It allows users to create a profile, add friends, send messages and join common interest groups.

Is Social Media the Most Important New Tool for Agricultural knowledge sharing?
When asked what one believes to be the impact of technology on agriculture, a standard and common answer might focus on scientific and technological developments that have been made in all areas of the agriculture industry. These developments include (but are certainly not limited to) genetic advancements in the livestock industry, bio-tech agronomic advancements (the implementation of genetically modified organisms in crops), the use of GPS technology in agricultural equipment, and the use of agricultural byproducts in alternative fuel sources. In essence, natural resources were provided to mankind; with time, mankind’s knowledge pertaining to feeding the world has developed in such a way that has ultimately helped to produce food, fuel, and fiber more efficiently. If someone had asked me five years ago what I believed to be the impact of technology on agriculture, most certainly, the scientific and technological developments which I previously described would have been the topics I used to give an answer. Today, however, my answer encompasses a very different concept. Although it is true that science and technology have drastically changed the agriculture (and will continue to make a significant impact on agriculture), advancements as results of technology will be for naught if agriculturalists do not overcome the current issue of agricultural illiteracy.
The power and impact of social media has not yet been fully realized; but already, organizations like PETA (People for the Ethical Treatment of Animals), HSUS, Farm Sanctuary, and many others have successfully harnessed the power of social media to do great harm to the agriculture industry. Negative images and messages falsely depicting agriculture have reached millions, if not billions, of internet users all over the world. For those individuals living in the city, a YouTube video posted by PETA may be all that person knows of agriculture. If that person thinks pigs are mistreated, that person might not want to purchase pork anymore. This could have a ripple effect and could potentially be a serious problem. The livelihoods of farmers everywhere are on the line. Not only do the social media actions of these activist groups have an impact on consumer choices, activist groups are gaining support from these consumers. As more and more support is gained for their cause, anti-agriculturalists build up strength to lobby for change in government regulations. Agriculture has been tasked with feeding 9 billion people by the year 2050 using fewer resources and less energy. If additional government regulations are imposed, this goal might be impossible to reach. I recognize the negative impact a simple tweet, blog post, Facebook post, or YouTube video could have on the industry I have chosen to work in for the rest of my life.

I also recognize the positive impact a tweet or online social media post could have. Today, many agriculturalists have to defend themselves with social media. Wouldn’t we make more of an impact if we were to start the conversation? Consumers want and need to know the truth about how their food is produced. The producer responsible for that consumer’s rib-eye steak or ear of sweet corn needs to be the one educating the public. Recently, farm families all across the United States have begun to recognize the importance of telling their stories. Stories about their family farm (eliminating the negative connotation of corporate farming), stories about how they started out in 4-H and FFA learning about animal stewardship (eliminating consumer fears of animal cruelty), or even just stories about what a farmer’s average day looks like. Farmers are sharing these stories through social media, and I believe that this is the start of a movement that will forever change the agriculture industry as we know it. Consumers need to know how and why we produce food the way we do, and internet technology is just the tool to help agriculturalists inform consumers. In order to continue utilizing advanced technologies in the field, agriculturalists will first need to harness the power of social media technology. The impact of that technology will be huge, and I am excited to see just how powerful this technology can be for agriculture.

The Effect of Social Media Activities on Network Information Accuracy of Individuals
Since recent years, we probably all noticed an explosion of usage and popularity of social media such as LinkedIn and Facebook. Already millions of individuals throughout the globe are frequent users of social media and have social networking internet sites accounts. Currently, there are many possibilities to engage in social media such as blogging and there are hundreds of social networking sites (SNS) each focusing on different interests and possibilities such as sharing information, networking or expressing feelings and thoughts (Cavazza, 2009). Social media become more popular each day and a frequent misconception made is that only teenagers make use of it. Currently, many large and well-known organizations world-wide use social media.

Besides the possibilities for business, individuals might extract much information from many of the available SNS about their connections and the structure of their network (Borgatti et al., 2009). Furthermore, Ellison et al. (2007) reported empirical support for the positive relationship between intensive Facebook use and indicators of social capital. Finally, according to Boyd and Ellison (2008) its uniqueness lies in the fact that SNS are making networks visible. However, it could still be asked if this is just for fun and games or does it yield ‘real’ benefits as well? It could be argued that above mentioned possibilities of social media are useful because networks are difficult to understand (Moore, 1992). Moreover, networks are generally complex concerning the fact that it is difficult to organize and keep track of relationships (Kilduff et al., 2008) and therefore it might be hard to understand networks in general.
Due to the complexity of understanding networks we also know that people tend to perceive networks and its structure incorrectly. For instance, according to Kumbasar et al. (1994) the perception of employees is that they have a more central position in the friendship network within the organization than is actually the case. Furthermore, more ‘small worldedness’ is perceived in networks than that it exists in reality (Kilduff et al., 2008). Finally, Casciaro (1998) argues that ‘people differ in their ability to perceive accurately the informal patterns of interpersonal relationships in their social groups, i.e. the group’s network structure’ (p. 331). Because of the fact that several SNS are giving information about direct and indirect links, this is becoming more visible for users. This is important since there is evidence that individuals having an accurate perception of advice-networks are perceived as more powerful than others in the organization (e.g. Krackhardt, 1990). Moreover, network information accuracy benefits individuals in terms of resource acquisition because of the understanding which connections in their networks grant them resource admission (Casciaro, 1998).

Challenges and opportunities of social media in extension
Social media use is not growing at a desired rate in rural India as there are multiple challenges that need to be taken care of to leverage the opportunities. The following table lists the challenges and opportunities of social media in extension (Table 2)
Table 1: Challenges and opportunities of social media in extension
Challenges Opportunities
Ensuring participation Few social media apps are available
without internet
Quality control and monitoring of posts Forming global/national interest groups is possible
Internet and IT infrastructure issues Reaching one to many
Satisfying heterogeneous users Greater engagement and dialogue
Institutionalizing social media Allows for integration of a wide range of stakeholders
Continuous engagement Can act as catalyst for resource
mobilization (technological, organizational, and financial
Skilled human resource to maintain social media interactions Measuring the impact – lack of capacity for tools and analytics that help monitoring and assessing the value of information Allocating time to update content Encouraging stakeholders to access resources through social media links (Source: Saravanan et al., 2015)
Knowledge management
As we have noted above knowledge is becoming a strategically important resource and a very significant driver of organizational performance (Yesil and Dereli, 2013). Either located in the minds of the individuals (tacit knowledge) (Polányi, 1966), embedded in organizational routines and norms, codified in technological devices (explicit knowledge) (Nonaka and Takeuchi, 1995), knowledge enables the development of new competences (Choo, 1998). Successful companies are those that consistently create new knowledge, disseminate this knowledge throughout the organization, and embody it in technologies, products and services (Gottschalk, 2007; Gaál et al, 2014). Knowledge management describes the processes of acquiring, developing, sharing, exploiting and protecting organizational knowledge to improve organizations’ competitiveness. Negroponte (1995) conceived the concept of “knowledge” as the most recent input factor for business organizations and a key to their future competitiveness.

A review of the research literature in Knowledge Management provides many definitions of knowledge and knowledge management distributed among numerous important journals, studies and books. Our research group adopted the definition of knowledge management utilized by KPMG (2003:4) namely: “knowledge management is a systematic and organised approach to improve the organisation’s ability to mobilise knowledge to enhance performance”.

Many organizations and institutions have recognized the importance of knowledge and knowledge management to the future performance of both businesses and society. For example, the report Europe 2020 sets out a new vision of Europe’s social market economy for the 21st century. One of the priorities it puts forward is the promotion of smart growth, which is, developing an economy based on knowledge and innovation. Such smart growth requires among others things the promoting of innovation and knowledge transfer, making full use of information and communication technologies and ensuring that innovative ideas can be turned into new products and services (European Commission, 2010).

The emergence of the knowledge economy and the recognition of knowledge as a key factor in the achievement of competitive advantage are making it critical to understand and develop effective approaches to knowledge management.

Organizations around the world have focused on knowledge management and have already developed knowledge management programs in order to improve their performance with varying degrees of success. Clearly one important set of activities involves the defining knowledge and constructing the metrics to assess how effectively an organization is managing (sharing) its knowledge (intellectual capital). The development of this definition and the creation of metrics is clearly challenging but is a necessary first step towards improving knowledge management practices since it has been cogently argued that one cannot improve what one cannot somehow measure (Gaál et al, 2008).

Although a standard global approach to knowledge management does not exist three general activities involved in knowledge management have been identified. These activities are integrated together into the overall knowledge management process. The three major activities are (Figure 1):
Knowledge capture and/or creation,
Knowledge sharing and dissemination,
Knowledge acquisition and application (Dalkir, 2005).

Knowledge sharing
Sharing is a common activity for everyone, but knowledge sharing within an organization is a complex and complicated issue. Knowledge sharing is the process by which knowledge of individuals is converted into a form that can be understood and used by other individuals (Ipe, 2003). Knowledge sharing refers to the task to help others with knowledge, and to collaborate with others to solve problems, develop new ideas, or implement processes (Cummings, 2004).

There are four factors that influence knowledge sharing (Ipe, 2003):
Nature of knowledge
Tacit form: located in the individual’s mind (Polányi, 1966)
Explicit form: embedded in organizational routines and norms, codified in technological devices (Nonaka and Takeuchi, 1995).

Motivation
Internal factors: perceived power (Gray, 2001) and reciprocity (Davenport and Prusak, 1998)
External factors: relationship with the recipient and rewards for sharing (Hall, 2001)
Opportunities
Formal: training programs, team works, technology-based systems
Informal: personal relationships and social networks
Culture of the work environment
Organizational culture determines values, beliefs, and work systems that could encourage knowledge sharing (Janz and Prasarnphanich, 2003)
There are three generations of knowledge sharing (Bellefroid, 2012):
First generation: the traditional way of knowledge sharing is the concept of codification (Hansen et al, 1999) and storage. This way can easily be supported by information technologies.

Second generation: focuses on the social component, personalization (Hansen et al, 1999), and the way people co-operate and communicate. Formal and informal opportunities can be used like mentoring, coaching or face-to-face meetings. Codification is mostly used as a starting point, were new employees can find out what employees know and what knowledge is available. Personalization is used to see the application of the available knowledge.

Third generation: social networks are the new ways to get in touch with experts and to search for knowledge outside the organization. Using social media tools enable less physical contact between employees.

Organizations have urgent need to pay specific attention to effective knowledge sharing, which is vital importance for their success and to achieve competitive advantage. Knowledge sharing can be materialized in written form through IT systems or via face-to-face communications. It is important for the next generation managers to provide opportunities for people to share their knowledge. Organizations have to stimulate a need to share knowledge among a group of people. When this need appears, physical or electronic spaces are likely to be used for knowledge sharing purposes (Huysman and Wit, 2004). About physical knowledge sharing several research has been done (Bock et al, 2005; Hansen et al, 2005, Quigley et al, 2007;).

As, the goal of Knowledge Sharing (KS) in social media is to distribute the right content to right people at right time. The system therefore must enable us quickly and effectively to find relevant information & expertise and that can aid into decision-making & problem solving. The concept of knowledge transfer is difficult to capture, because there is no clear distinction between the transfer of knowledge and the creation of new knowledge (Bresman et al., 1999). However, the biggest challenge in fostering a virtual community is the supply of knowledge, namely the willingness to share knowledge with other members. Extension workers intent to share knowledge because they feel that sharing what they know will make them expandable or that their knowledge on any given subject is what makes them unique in social platforms. They are also intent to participate in virtual communities, especially in professional virtual communities for seeking knowledge to resolve problems at work. According to the ‘Social Exchange Theory’ (Thibaut, et al., 1959) participants in virtual communities expect mutual reciprocity that justifies their expenses in terms of time and effort spent sharing (intrinsic motivation) their knowledge. Through close social interactions, extension workers are able to increase the depth, breadth, and efficiency of mutual knowledge exchange.
The use of social media in knowledge sharing though is not a new concept in the context of business enterprises, its adoption and use for professional knowledge sharing in agriculture sector, especially in a developing country context certainly holds some values, and hope to add a new dimension in extension communication process. Despite the social media is designed as a hedonic information system, its use for utilitarian purposes such as for business and work are well known. As it, on one hand, helps to develop strong social capital among the employees, on the other hand, users intentionally or un-intentionally share or exchange professional/job-related information. Thus, facilitates knowledge sharing among users. Therefore, this research is intended to determine extension workers’ intention to adopt social media in agricultural knowledge sharing.

Statement of the Problem
The biggest open area of augmentation benefit giving in Bangladesh is the Department of Agricultural Extension (DAE). The bleeding edge augmentation officers prevalently known as Sub-Assistant Agriculture Officer (SAAO) of DAE work in piece level (the most minimal regulatory unit of expansion benefit/sub-unit of Upazila) and straightforwardly exchange innovation to the ranch level. Most farmers access information from extension workers. The number of extension workers is comparatively lower than the farmer numbers; hence the need for innovative services to address this gap (Gakuru et al., 2009). The agriculture sector in developing countries is becoming increasingly knowledge intensive. Researchers at the global, regional, and national levels continue to generate new information and deliver new solution for raised problem. As agriculture systems become more complex, farmers’ access to reliable, timely and relevant information sources becomes more critical to their competitiveness. Information must be relevant and meaningful to farmers, in addition to being packaged and delivered in a way preferred by them (Diekmann, Loibl & Batte, 2009). The success of extension service is therefore largely depends on their knowledge, skills and performance to provide quality extension service to its clients. For seeking information and updating their knowledge and skills, extension workers use both interpersonal communication such as higher officials (Upazila Agriculture Officer (UAO), Agricultural Extension Officer (AEO) at upazila or district level, and mass communication media like printed materials (newspaper, bulletin, leaflet, other farm publication), radio and Television. Nevertheless, recent advancement of communication media especially mobile phone, computer, the Internet, digital information repositories likes social media are also regarded as the important information sources for extension workers to obtain necessary information and develop their capacity in providing extension service. The extension workers need to understand farmers’ opportunities and problems and help them finding the best solutions for their agriculture. De Silva and Ratnadikwara (2008) state that a two-way process enables extension professionals to share lessons and best practices related to their services, thus incorporating their knowledge base as well. Social media is increasingly being used as a medium of sharing information and creating awareness. Platforms like Facebook, Twitter, YouTube and blogs have been used to engage with various audiences. The users generate and shape the content.

Today, in many countries, social media are being used by farmers and extension professionals, not only as their personal communication medium, but also, to provide access to information though sending messages service (SMS), multimedia messages service (MMS), posting agricultural contents, photos and videos on the different agricultural group. Hence, the main aim of this study is to present the findings of a survey carried out in Comilla district, about the use of social media by extension professionals, specifically as a mean for sharing to agricultural information which ultimately help them to achieve the objectives of DAE and improve living standard of rural people in general and the farming community in particular by increasing agricultural production. In such manner, it is relevant to know the appropriate response to the accompanying inquiries:
What factors influence extension professionals to use social media to share agricultural knowledge?
To what extent extension professionals use social media in updating their capacity in agricultural service delivery?
What are the significant influence of the selected factors to extension professionals’ use of social media and their perceived capacity development in agricultural service delivery?
What the problems extension professionals’ faced in sharing work-related information using social media?
With regards to the previously mentioned questions, the researcher embraced an study entitled, “Use of Social Media in Agricultural Knowledge Sharing by the Extension professionals'”
Objectives of the StudyBased on the issue explanations made in area 1.3, the accompanying research goals were detailed to direct the research:To identify the factors that might influence extension professionals’ to adopt/use social media in agricultural knowledge sharing,
To identify extension professionals’ intention to use social media in agricultural knowledge sharing,
To explore the influence of the identified factors (objective 1) on the extension professionals’ intention to adopt/use social media in agricultural knowledge sharing.

Justification of the StudyUse of social media is very important due to it provides a quick and responsive network for people involved in agriculture to gather and exchange information. It allows immediate dissemination of important emerging issues and the sharing of positive information among producers and consumers of agricultural products and by providing science-based plant nutrition and fertilizer use information to industry, farmers, agricultural and environmental leaders, scientists, and public policy makers. Yet adoption of social media in aspect of agricultural knowledge sharing by extension workers in Bangladesh seems to not so popular. However, this study is important because social media as a medium is being used as a tool for informing, educating and persuading the masses alongside traditional mediums. Hence this study seeks to find out how effective social media is in communicating to agricultural extension workers and how this can bring about development in the agriculture sector. The study is also necessary in order to understand the efficiency of social media platforms in communicating to its target audience. It will be useful to researchers, scholars and organizations who are interested in understanding the efficiency of social media as a medium of communication. On the other hand, this research may facilitate to identify the factors that influence extension workers to adopt/use social media in agricultural service and extension workers’ intention to use social media in agricultural knowledge sharing. The identified factors may be used in fostering professional virtual communities of agricultural knowledge sharing to track infectious disease outbreaks, aid in natural disaster response, product price information about new released varieties and technologies which may motivate/help farmers to increase agriculture production and assure the food security of Bangladesh. From academic perspective, findings of this study and the methodology used in this study would inspire other researchers to conduct further investigation. Finally, the findings of this study will hope to provide insights to the policy makers on how to develop effective ICT-based solutions for effective extension service in Bangladesh.

Scope and Limitations of the StudyThis study was driven with a view to surveying the utilization of social media in agricultural information sharing by the extension experts. An endeavor was likewise made to discover the issues looked by the SAAOs, AEOs and UAOs to utilize social media in refreshing their experts’ aptitudes and a similar time information too. Nonetheless, with a specific end goal to make the investigation sensible and significant, the accompanying confinements have been considered all through the study:
The study was directed in five upazilas to be specific Debidwar, Brahman-para, Burichong, Chandina and Comilla Sadar under Comilla locale.
There are numerous factors that might influence extension professionals’ to knowledge sharing through social media, however only few factors which deemed important and consistent with the study context were considered for this study.
While assignment and obligation of expansion experts are differed, just front level augmentation workers (e.g., SAAOs) were considered as the respondents of this study.

This study utilized self-reflected estimated of perceptual variables which may influence certain interpretations of the findings.

There are different part of limit building performed by the extension experts, however just few of them were considered for this study.
Given the research interest, determining professionals’ capacity development through ICTs, longitudinal data might be a possible alternative to test the hypothesized relationships. However, considering the time and resources constraints, only cross-sectional data were used to test the model.

Assumptions of the StudyThe researcher made the accompanying suspicions undertaking this study:
The SAAOs/AEOs/UAOs incorporated into the example of the study were sufficiently able to fulfill the quarries outlined by the researcher.

The data outfitted by the respondents were right and illustrative of the populace and free from any inclination.
The perspectives and suppositions outfitted by the SAAOs/AEOs/UAOs incorporated into the example were the agent perspectives and conclusions of all the SAAOs/AEOs/UAOs of Comilla region in Bangladesh.

Environmental conditions and organizational procedures under which the SAAOs work are generally similar throughout the study area.

Ecological conditions and authoritative methodology under which the SAAOs/AEOs/UAOs work are for the most part comparative all through the study territory
Data furnished from the respondents were normally distributed.
Findings of the study will, for the most part, be connected to different parts of the nation with the comparable individual, financial and social conditions.

Definition of the Terms
This study intended to determine extension professionals’ perceived capacity development through ICTs and the salient factors that might affect their ICTs use behavior. Before further discussion, some key concepts and definitions of the terms are presented in this section.

Concept Definition
Social media Social media refers to the internet-based digital tools for sharing and discussing information among people. It refers to the user generated information, opinion, video, audio, and multimedia that is shared and discussed over digital networks (Andres and Woodard, 2013)
Extension professional Agricultural extension professionals incorporate every single proficient staff working in the extension organization who give cultivate related expansion support to its customers. Be that as it may, just front-level augmentation experts (i.e., SAAO) were considered as the respondents of this study.

Age Age of the respondents is defined as the period of time from their birth to the time of interview.

Service experience It referred to one’s entire duration of service from the date of first joining in the Department of Agricultural Extension (DAE) till the date of interview.

Reciprocity (Kankanhalli, et al. 2005) The belief that current contribution to social media would lead to future request for knowledge being met (Davenport and Prusak 1998)
Self-development
( Kankanhalli, et al. 2005) Self-development refers to the activities that improve an organization’s ability to achieve its mission or a person’s ability to define and realize his/her goals or to do his/her job more effectively. Here, Self-development of extension professionals is defined as their perceived ability to upgrade their skills and knowledge by using of social media.
Reputation (Kankanhalli, et al. 2005) The perception of increase in reputation due to contributing knowledge to social media (Constant et al 1996; Kollock 1999)
Communication efficacy
(Compeau ; Higgins, 1995) It refers to the judgment of one’s ability to use a technology (e.g., computer) to accomplish a particular job or task. Communication efficacy in this study incorporates one’s belief in his ability to upgrade his knowledge and skills to perform a job better using social media.
Relationship building(Bock, et al. 2005) The degree to which one believes one can improve mutual relationships with others through one’s knowledge sharing.
Enjoyment (Kankanhalli, et al. 2005) The perception of pleasure obtained from helping others through knowledge contributed to social media (Wasko and Faraj 2000)
Subjective norms (Fishbein and Ajzen 1975, p. 302) The degree to which one believes that people who bear pressure on one’s actions expect one to perform the behavior in question multiplied by the degree of one’s compliance with each of one’s referents. Therefore, this study defined subjective norms as the extent to which an extension professional perceives that her peers, colleagues and important others believe she should use ICTs.

Intention to share
Knowledge (Bock, et al. 2005) Explicit Knowledge: The degree to which one believes that one will engage in an explicit knowledge sharing act
Implicit Knowledge: The degree to which one believes that one will engage in an implicit knowledge sharing act

CHAPTER IIREVIEW OF LITERATUREThe motivation behind this chapter is to review the aftereffects of a portion of the past examinations and prominent articles having pertinence to this investigation. This examination is chiefly identified with the assurance of saw limit working of SAAOs through web-based social networking. The analyst attempted to gather required data by intensive seeking of related thesis, writing, periodicals and the Internet. In any case, utilization of social media by experts in agriculture for limit building or for expanding work execution was infrequently accessible. To address the research objectives, this study therefore reviews the existing literature which deemed relevant to the phenomenon of interest such as IT adoption literature, organizational behavior literature, and proposes a theoretical understanding of the current investigation into the three sections. The first section is worried about the review of literature on the concept of social media and shows how web-based social networking encourage in agricultural information sharing. The second section identifies the salient factors that might influence extension professionals’ use of social media for agricultural information sharing. The third section proposes a conceptual model of this study based on the discussion presented in first two sections. The accompanying areas in the audit of related writing introduced by the goals of the investigation and sorted out as indicated by the significance of the objectives.

2.1 Use of social media and its Relation to knowledge sharing
This area first exhibits the concept of social media and after that talks about the significance of web-based social networking especially for extension professionals in agricultural information sharing. Ultimately, it portrays how web-based social networking can assume a crucial part to create extension professionals’ quality through knowledge sharing.

2.1.1 Social media: new generation tools for “agricultural extension”?
Though Social Media applications can be effectively used by extension and advisory services, lack of awareness and skill about its use currently constrain its widespread use. Moreover the organizational culture within extension organizations also restricts exploitation of its full potential by extension professionals. Developed countries have started adopting and harvesting the benefits of social media for agricultural extension for some time. For example, US Co-operative extension system and universities have adopted social media for connecting its clients especially through Facebook, twitter, pinterst, google+ and youtube (http://www.extension.org/). The AgChat (Twitter online discussion group by the AgChat Foundation) started in 2009 by a group of American farmers is widely used in USA, UK, Australia and Ireland for facilitating discussions of industry issues between farmers and agribusinesses has 50,200+ followers and 25,000 tweets (https://twitter.com/agchat). Many US land grant universities developed social media guidelines for extension. Considerable number of articles written by the extension experts from the co-operative extension system and US universities emphasises the potential role of social media in extension.

Australian Government’s Caring for Our Country program funded the project on “Social Media in Agriculture” to explore the use of social media (You Tube, Vimeo, Facebook, Twitter, RSS, etc.) as an extension tool (http://agex.org.au/project/social-media-project/). Research findings from Ontario, Canada indicated that (since 2008) individuals and organizations in the agri-food and rural sectors are including social media tools (Twitter, blog, facebook etc.) in their communication for innovation (Chowdhury and Hambley, 2013).

Developing Countries:
Social media use has gained pace in the developing countries too, especially with Facebook. Some examples are given in the table below:
Table 2: social media usage for agricultural knowledge sharing world wide:
Group/Community/Pages Description Target users Region Member
Use by farmer
Livestock Information and Marketing Centre(https://www.facebook.com/groups/Livestock.TN/ Members (farmers, extension personnel, scientists, market functionaries, consumers, local leaders, etc.) of this group share information related to livestock production, management, marketing, etc. A separate page is also on facebook related only to marketing of livestock. (https://www.facebook.com/Livestock.Market) Agricultural stakeholders related to livestock Tamil Nadu, India
49483
Mkulima Young (Young Farmer)
(https://www.facebook.com/mkulima.young) This page is an information sharing platform for young farmers started Joseph Macharia, a young farmer himself. Mostly agro-advisory and market information are shared.

Kenya 39082
Natural farming Development Centre
(https://www.facebook.com/groups/NaturalFarmingTN/) .Members of the group share information related to organic farming, permaculture, hydroponics, aquaponics, Natural Repellents, etc. Farmers interested in organic and zero budget agriculture Tamil Nadu, India
16 268
Turmeric Farmers’ Association of India
(https://www.facebook.com/turmeric.farmers) This page was created by turmeric farmers to stabilize price of turmeric in the market. Till date, the farmers connect through the page and share information to keep turmeric price stable and increase marketing opportunities of turmeric. Turmeric farmers
India
2911
National Ecological Producers Association (APNE)
(https://www.facebook.com/anpe.peru) Information related to ecological farming is shared through the page. Farmers
Peru
3061
Use by extension centers
Krishi Vigyan Kendra, Namakkal(https://www.facebook.com/krishi.namakkal) Krishi Vigyan Kendra, Namakkal communicates information related to farmers’ training programmes, availability of inputs etc. Subject Matter Specialists of KVK, farmers, and other agricultural stakeholders Namakkal, Tamil Nadu, India
1464
Use by extension professional networks
Agricultural Extension in South Asia (AESA)
(https://www.facebook.com/groups/428431183848161/) Members post links to relevant publications on extension and advisory services, announcements of workshops and conferences, major policy decisions on extension, reports of meetings and workshops relevant to the broader theme of extension Agricultural Extension stakeholders South Asia
7 550
Global Forum for Rural Advisory Services (GFRAS)
https://www.facebook.com/groups/gfras This page provides information related to advocacy and leadership on pluralistic, demand-driven rural advisory services. RAS Professionals and others
Global
1 794
Use by extension personnel
Vivasayam Karkkalam
(Let us Learn Agriculture)
(https://www.facebook.com/groups/madhualan)
Mr. Madhu Balan, a public extension officer started facebook group to cater the information needs of famers in 2012. This group, exchange information on improved farm technologies, initiates discussion with other farmers and extension personnel, share information and photos on best practices by other farmers, government schemes, etc. Question and answers, information on Terrace garden, hydrophonics are most discussed topics in this group.

Farmers and others those
Who are interested in agriculture
Tamil Nadu,
12 118
All these examples presented above are initiated by individuals, small groups and networks to disseminate information by and for agricultural stakeholders through social media. The number of followers/members of these pages, communities and groups are increasing every day and many of them are professionals. Social media use in agriculture is not restricted to any specific age group but users belong to all age groups. While Twitter is a more preferred platform in developed countries, Facebook dominates in developing countries. While farmers in developed countries are active in social media to tell their stories and connect with their clients, in the developing countries, these efforts are scattered and there are only very few cases where extension professionals and farmers participate actively in social media.

Fig.3 Showing facebook group
Challenges in using social media for agricultural extension in the developing countries
1. Passive users: A review of the activities in most of the groups/communities/pages indicated in table 1 shows that most of the users are very passive and only very few are pro-active. While many visit the group pages, only few posts, share and discuss ideas and issues.

2. Irrelevant information: Along with useful things, frequently there is irrelevant information also posted in the social media which increases the need of monitoring.

3. Participation of agricultural stakeholders: Other than groups like Turmeric Farmers Association of India which is formed by farmers, other groups like AESA, YPARD, etc. are used actively only by specific type of users and participation of farmers is almost nil even though they are for all agricultural stakeholders.
4. Infrastructure issues: Limited ICT infrastructure and internet connectivity is still a major issue in rural areas of most developing countries.
5. Mindset of users: Many users still believe that social media is “not for serious business”. It is for just to share personal photos and general information.

2.1.2 The concept of social media
The internet has impacted communication. It has been considered as an archive for information whereby people can obtain information. According to Dennis and Merill (2010) the internet is a marvel because according to findings its users rose from under 10% of the adult population in 2005 to an estimated 66.5% in 2008 or some 281 million Americans. Most people use the internet for personal communication through email, social media sites and access to information. Social media refers to the internet-based digital tools for sharing and discussing information among people. It refers to the user generated information, opinion, video, audio, and multimedia that is shared and discussed over digital networks (Andres and Woodard, 2013). Merriam-Webster (2015) defines social media as forms of electronic communication through which users can create online communities to share information, ideas, personal messages and other content. The definition of Ahlqvist et al. (2008) is focussed on three basic components – content, communities and Web 2.0 and operationalises social media as the interaction of people and also to creating, exchanging and commenting contents in virtual communities and networks.
According to Michelle Chmielewski (2011), social media is not about what each one of us does or says, but about what we do or say together, worldwide, to communicate in all directions at any time by any possible digital means. Social media are basically digital technologies facilitating communication of user generated content through constant interaction (Terry, 2009; Kaplan and Haenlein, 2010). In a nut shell, social media are web based tools of electronic communication that allows users to interact, create, share, retrieve, and exchange information and ideas in any form (text, pictures, video, etc.) that can be discussed upon, archived, and used by anyone in virtual communities and networks. Aspects of social media that makes them an important and accessible tool in development communication are their easy access through mobile phones, mass-personal communication and mass-self communication, a larger set of weak ties to ensure receipt of novel ideas, high degree of connectedness, and link ability and content sharing across multiple platforms (Hemsley and Mason, 2013). The internet and the World Wide Web are a remarkable invention that allows access to an almost infinite storage of information. After initial skeptism some leaders of media industries proclaimed the internet to be the universal information highway and were bullish on its development.
They imagined the benefits of interactivity as an unparalled platform for delivering their content (whether information, entertainment, opinion or advertising) almost effortless and without the costs associated with printing and broadcasting. The new media would be interactive, with instant feedback from consumers as well as a constantly updated treasure trove of information (Dennis &Merill, 2010).Social media is a one stop shop for information whereby the users can read and also contribute to the content. It is convenient to those who need information instantly or do not have easy access to information.
Social media is a collection of online technologies that allow users to share insights, experiences and opinions with one another. The sharing can be in the form of text, audio, video or multimedia (Safko & Brake, 2009). Tang, Gu & Whinston (2012) state that the benefits of participating in social media have gone beyond social sharing to building reputations and bringing in career opportunities and monetary income. According to Kietzman, Hermkens, McCarthy and Silvestre (2011) social media platforms focuses on some or all seven building blocks that is; identity, sharing, conversations, relationships, presence, groups and reputation. Different social media activities are defined by the extent to which they focus on some or all of these blocks.
Social media provides opportunities for organization to interact with their publics/personal in real time. This is important because feedback enables organizations or companies to make quick decisions and the same time gather knowledge. Social media is also cheaper in the long run. According to Kiertzman et al. (2011) due to mobile and web based technologies social media creates highly interactive platforms through which individuals and communities share, co-create, discuss and modify user-generated content. It introduces substantial and pervasive changes to communication between organizations, communities and individuals.

Social media has revolutionized communication whereby it has managed to surpass traditional gatekeepers in traditional media that is editors and other decision makers who set the agenda. Nevertheless social media has not overthrown traditional media and is complementing traditional media in agenda setting. Traditional media has been the main medium for companies to reach their audiences and there has been a great deal of control which is avoided on social media. Social media is dominated by user generated content. Social media is an evolutionary stimulus because users not organizations or the traditional news media now control the creation and distribution of information. Users bypass the traditional information gatekeepers (Coombs, 2012).

The traditional mass media have attempted to reach as many readers and viewers as possible joined with more targeted new media players who sought a particular segment of the population, including those with quite specialized interests anywhere in the world. (Dennis & Merill, 20010).

Old media are largely geographic, aimed at people in particular physical places, whereas new media are demographic, seeking clusters of like-minded individuals with similar interests and passions, much like specialized magazines but with broader reach and genuine interactivity (Dennis & Merill, 20010). Social media has allowed for the crossing of boundaries whereby people of different geographical regions locally and internationally have been able to exchange ideas on various forums. This has allowed for necessary conversations to take place. Makinen and Kuira (2008) as quoted by Odero (2013) state that social media was an alternative media for citizen communication but it was also used as a channel for biased information.

2.1.3 Research on knowledge sharing and social media tools
Several research has been conducted about using social media and Web 2.0 in the workplace for sharing knowledge. Paroutis and Saleh (2009) investigated the key determinants of knowledge sharing and collaboration using Web 2.0 technologies by exploring the reasons for and barriers to employees’ active participation in its various platforms within a large multinational firm. Their study identifies the key determinants of knowledge sharing and collaboration using Web 2.0 technologies by exploring the reasons for and barriers to employees’ active participation in its various platforms within a large multinational firm. Using insights from both users and non-users of Web 2.0, the following four key determinants were identified: history, outcome expectations, perceived organizational support and trust.
Dumbrell and Steele (2014) presented an informal knowledge management framework based on the system capabilities present in social media technologies as well as the requirements of older adult users. The system capabilities distinctive to social media technologies are: public peer-to-peer sharing, content evaluation amongst peers, and the “push” nature of these systems.
Behringer and Sassenberg (2015) studied the relation between importance of knowledge exchange, deficits in knowledge exchange, perceived usefulness of social media for knowledge exchange, as well as social media experience on the one hand and the intention to use knowledge exchange technology on the other hand. The results showed that the interplay between the importance and deficits concerning knowledge exchange, perceived usefulness of social media for knowledge exchange, and experience in social media use jointly affected the intention to apply social media for knowledge exchange after their implementation.
Another study (Sigalaa and Chalkiti, 2015) investigates the relation between social media use and employee creativity by adopting a knowledge management approach in order to consider the influence of social networks and interactions on individuals’ creativity. Their findings highlight the need to shift focus from identifying and managing creative individuals (micro level) and/or organizational contexts (macro level) to creating and managing creative social networks (meso level). The use of social media for externalizing, disseminating and discussing information with others within various social networks as well as for combining and generating shared (new) knowledge can further trigger, enrich and expand the employees’ individual cognitive abilities and provide them with stimuli for generating and (co)-creating more and newer ideas/knowledge.

2.1.4 Social media and its’ roles to knowledge sharing:
A definitive objective of social media tools is making a dynamic and knowledge network community that people can trade and offer their significant data which is called knowledge sharing. Different investigations have demonstrated that information can be better and adequately imparted to the guide of online networking apparatuses which have gone far in affecting all parts of human lives and attempts. Sonja and Carina (2012) characterized web-based social networking as online applications for correspondences being encouraged between aggregate individuals and organizations. Likewise, Abdulsalam and Azizah (2012) characterized web-based social networking as the progressive arm of the web that gives better approaches for making content, teaming up, communicating, and sharing data online in an open social condition. They are an assortment of innovations that help the social parts of the Internet as a channel for correspondence, joint effort, and communication, which is described as Web 2.0 assets that underscore dynamic cooperation, network, coordinated effort, and in addition sharing of information and thoughts among clients. Web-based social networking innovations, for example, web journals, wikis, podcasts, RSS channels, and long-range informal communication can be portrayed as ‘social programming’ since they are seen as being particularly associated, and clients team up to create open substance to the general population Van (2009) opined that applying this kind of online networking apparatuses in the association will help individuals to help each other to participate in information administration and learning sharing. Kim and Abbas (2010) analyze the elements of the web 2.0 in scholastic libraries, in view of information administration and learning sharing point of view. Their discoveries demonstrate that the web 2.0, RSS devices and blog utilized especially in scholastic libraries and Tagging devices have been generally utilized by understudies. Likewise Wahlroos (2010), in his proposal entitled “Online networking as a type of authoritative information sharing: a contextual investigation on representative cooperation at Wartsila”, researched the part of Social Media Tools is in the sharing of learning. The consequences of his examination demonstrated that individual elements (utilizing of this instrument in individual life), authoritative elements (exercises of chiefs and colleagues and hierarchical aides) and specialized factors, for example, specialized aptitudes in the utilization of Social Media Tools is compelling in sharing of learning. Asemi and Talkhabi (2012) in an examination, researched the level of mindfulness, use and dispositions of graduate understudies of Sharif University about social intuitive media web 2.0 and in the long run presumed that among the seven gatherings of SMT in this investigation (counting SNT, blogging instruments, miniaturized scale Blogging devices, SBT, IVShT and video conferencing apparatuses), wiki and smaller scale blogging are dedicated most extreme and least clients to itself, separately. Electronic media viz. mobile phone, computer, Internet, online databases, web and mobile application can be very useful to get information even to the remote areas where it is very hard to make direct contact (Samanta, 1986). Internet-based medium is a fascinating source of information (Mahtab and Mokhtarnia, 2009) which allow extension workers to access to a knowledge resource anytime from anywhere without much delay and depending on the traditional information sources. Social media has also been seen as a performance enabler in the workplace. Considering these arguments, it can be concluded that professionals’ use of social media enable them to retrieve, process and disseminate information independently and therefore promote effective extension service to its clients.
2.2 Identification of the Salient Factors of Social Media Use by Extension Professionals:
Understanding extension experts’ utilization of social media in agricultural knowledge sharing was the key focal point of this study. Assessed introduced in Section 2.1.3 as of now uncovers social media roles to share knowledge in work setting. In this manner, it can be reasoned that utilization of social media would be a compelling option for professionals to overhaul their insight and abilities alongside other conventional methodologies. Be that as it may, it is essential to recognize what drives professionals to utilize social media in agricultural knowledge sharing.
Brown and Duguid (2001) suggest that knowledge flows are best understood by examining how work is actually performed and thinking about knowledge and learning as an outcome of actual engagement in practice. When individuals have a common practice, knowledge readily flows across that practice, enabling individuals to create social networks to support knowledge exchange (Brown and Duguid 2000). Brown and Duguid suggest that there are two practice-related social networks that are essential for understanding learning, work, and the movement of knowledge: communities of practice and networks of practice. These researchers conclude that the key to competitive advantage is a firm’s ability to coordinate autonomous communities of practice internally and leverage the knowledge that flows into these communities from network connections (Brown and Duguid 2000, 2001). A community of practice consists of a tightly knit group of members engaged in a shared practice who know each other and work together, typically meet face-to-face, and continually negotiate, communicate, and coordinate with each other directly. In a community of practice, joint sense-making and problem solving enhances the formation of strong interpersonal ties and creates norms of direct reciprocity within a small community (Lave 1991; Lave and Wenger 1991; Wenger 1998). In contrast, networks of practice consist of a larger, loosely knit, geographically distributed group of individuals engaged in a shared practice, but who may not know each other nor necessarily expect to meet face-to-face (Brown and Duguid 2001). Networks of practice often coordinate through third parties such as professional associations, or exchange knowledge through conferences and publications such as specialized newsletters. Although individuals connected through a network of practice may never know or meet each other face to face, they are capable of sharing a great deal of knowledge (Brown and Duguid 2000). With recent advances in computer mediated communications, networks of practice are able to extend their reach using technologies such as websites, electronic bulletin boards, and e-mail lists. Building upon Brown and Duguid’s (2000) general description of networks of practice, we define an electronic network of practice as a special case of the broader concept of networks of practice where the sharing of practice-related knowledge occurs primarily through computer based communication technologies. While many networks of practice are increasingly using electronic communication to supplement their traditional activities, electronic networks of practice differ from networks of practice due to the impact of technology on communications, which may result in different dynamics (DeSanctis and Monge 1999). More formally, we define an electronic network of practice as a self-organizing, open activity system focused on a shared practice that exists primarily through computer-mediated communication.

On the other hand, the types of social media platforms users in agricultural extension service delivery highlights the state of social media in extension service delivery with respect to the stakeholders, and emphasizes the kind of targeted audience and the needs needed to be addressed.
Despite the current globally reported average satisfactory level of social media platforms’ membership/followership by the stakeholders in agricultural extension service delivery, 1001-10,000 clients (25.1% and highest) are reached (Suchiradipta and Saravanan, 2016). On the use of social media for agricultural information purpose, stakeholders mostly either share or find information rather than discuss, suggest or promote a technology (innovation). An evidence to this is presented in Figure…

Figure. Use of social media for agricultural information purpose
Source: Suchiradipta & Saravanan (2016)
On the other hand, stakeholders (mostly farmers, extensionists, NGOs, business men and administrators amongst others) look for a variety of information on social media. A study conducted by Kuria (2014) in Kenyan community of lower Kabete under Kiambu County reported that audience (farmers) usually seek different forms of agricultural information on social media (Table 3).

Table:3 What people seek in social media:
Information Sought Mean Standard Deviation
Technological information 3.701 0.9431
Educational and training information 3.913 0.5423
Business and trade information 3.176 0.8612
Government agricultural policies and plans 3.113 1.0617
Weather condition and Environmental information 3.363 1.2610
Variety of seeds 2.984 0.9745
Agrochemicals 3.853 0.6734
Credit facilities, source, terms and conditions 2.152 1.0080
Market trend, price, and stock available 2.357 0.6834
Source: Kuria, 2014
In essence, the time and place have come for social media in this information age and that agricultural extension service delivery is gradually blending into the trend.

2.3 The Conceptual Model and Hypotheses Development-85725bottom
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Conceptual framework is the foundation for understanding the research issues and linkage among different variables. It helps as guiding principles for analyzing the research issues. It also helps easy visualization of the relationship between the dependent and independent variables. The study tried to focus towards use of social media in agricultural knowledge sharing by the extension professionals. A dependent variable may be influenced and affected through interacting forces of many characteristics in his surroundings. The conceptual framework of the study has been presented in Figure 1. The model depicts that extension professionals’ efficacy is positively influenced by their Social media use which however contingent upon seven independent factors viz. Reputation, Reciprocity, Relationship Building and Communication efficacy (Extrinsic motivation) and Self-development, Enjoyment and Subjective norms (Intrinsic motivation) were controlled in the model.

Figure 2. SEQ Figure * ARABIC s 1 1 The conceptual model of this study
2.3.1 Reputation and social media use:
In most organizations today, the importance of reputation is expanding as customary contracts amongst organizations and representatives in view of the length of administration dissolve (Ba et al. 2001; Davenport et al. 1998). In such working environments, knowledge contributors can benefit from showing others that they possess valuable expertise (Ba et al. 2001). This earns them respect (Constant et al. 1994) and a better reputation (Constant et al. 1996). Therefore, knowledge contributors can benefit from improved self-concept when they contribute their knowledge (Hall 2001; Kollock 1999). Employees have been found to share their best practice due to a desire to be recognized by their peers as experts (O’Dell and Grayson 1998). People who provided high-quality technical knowledge have been found to enjoy better prestige in the workplace (Kollock 1999).

While this discussion suggests a positive relationship between reputation and social media by knowledge contributors, the relationship may be contingent on pro-sharing norms. When strong teamwork and collaboration norms prevail, knowledge contributors may not require extrinsic benefits (Nahapiet and Ghoshal 1998) such as image in order to contribute knowledge. Under such conditions, knowledge contributors are probably going to contribute their insight to social media regardless of whether advantage as enhanced reputation is absent. On the other hand, weak pro sharing norms can make reputation a notable spark for knowledge contribution.

H1: With the increase of the extent of social media use by extension professionals, their reputation in the organization is increased.
2.3.2 Reciprocity and social media use
Reciprocity has been featured as an advantage for individuals to participate in social exchange (Blau 1964). It can serve as a motivational mechanism for people to contribute to discretionary databases (Connolly and Thorn 1990). Reciprocity can go about as advantage for knowledge patrons since they expect future assistance from others in lieu of their contributions (Connolly and Thorn 1990; Kollock 1999). Earlier research proposes that individuals who share information in online groups put believe in reciprocity (Wasko and Faraj 2000). Further, analysts have watched that individuals who frequently helped other people in virtual groups appeared to get help all the more immediately when they requested it (Rheingold 2000). These arguments suggest a positive relationship between reciprocity and social media usage by knowledge contributors, but the relationship may be contingent on pro-sharing norms. At the point when pro-sharing norms standards are solid, knowledg patrons may share their insight without a requirement for extraneous advantages (Nahapiet and Ghoshal 1998) such as reciprocity. In such a climate, knowledge contributors are likely to contribute their knowledge to social media even in the absence of reciprocity benefits. Conversely, when pro-sharing norms standards are frail, reciprocity might be a striking helper for knowledge patrons
H2: Individuals guided by a norm of reciprocity will contribute more helpful responses to social media usage by knowledge contributors
2.3.3 Relationship building and social media use
Constant et al. (1994) and others (Blau 1967; Organ and Konovsky 1989) argue that at the point when two people are influenced by their social and hierarchical settings, particularly where unspecified agreeable yields, for example, knowledge are exchanged, the social exchange relationship is a major determinant of their attitudes. Social exchange, particular from economic exchange, builds up o bonds of friendship with or potentially super appointment over others, and causes diffuse, unspecified obligations (Organ and Konovsky 1989). The worry is basically with the relationship itself, and not really any extraneous advantage that may specifically take after (Blau 1967).Along these lines, representatives who trust their common associations with others can enhance through their knowledge sharing, and who are working based on their want fairness and reciprocity (Huber 2001), are probably going to have uplifting states of mind toward knowledge sharing through social media.

H3: The greater the anticipated reciprocal relationships are the more favorable the attitude toward knowledge sharing through social media.

2.3.4 Communication efficacy and Social media use:
Organizations are increasingly using social media to improve their internal communication. When successfully implemented, such initiatives can have a dramatic impact on internal efficiency, team collaboration, innovation, organizational alignment, and cultural transformation (Amy et al. 2014). Prior research shows that within a corporate cultural background with the characteristics of: high level of trustworthiness, appreciation of teamwork, knowledge distribution, friendly and family atmosphere, corporate-goals that are identified by employees, various established internal and external communication-channels, close bonds among colleagues; the use of SM– internal-communication-platforms by employees already affectively committed to the company, positively and indirectly affects most of the work (Allen & Meyer 1990). This connection is described as indirect because affective organizational commitment (AOC) antecedents are affected only through SM–internal-communication-platforms’ impact on internal communication’s procedures. On the other hand, in the early days of SM–internal-communication-platforms’ use, top-managers’ embrace it more enthusiastically than employees because they are really preoccupied with communication and retain high expectations for internal-communication’s improvement after all staff is fully implemented with SM–internal-communication-platforms.
H4: The higher the individual’s Communication efficacy, the higher the use of Social media.
2.3.5 Enjoyment and use of Social media
This benefit is derived from the concept of altruism. Altruism exists when individuals get inherent satisfaction from helping other people without expecting anything consequently (Krebs 1975; Smith 1981). Despite the fact that there might be not very many examples of absolute altruism (including outright absence of self-worry in the inspiration for a demonstration), relative selflessness (where self-concern assumes a minor part in propelling a demonstration) is more predominant (Smith 1981). Knowledge contributors may be motivated by relative altruism based on their desire to help others (Davenport and Prusak 1998). Earlier research demonstrates that knowledge donors pick up fulfillment by showing their altruistic behavior (Wasko and Faraj 2000). Such fulfilment comes from their inherent satisfaction in helping other people (Ba et al. 2001; Constant et al. 1994; Constant et al. 1996). Knowledge givers who infer delight in helping other people might be more disposed to contribute information to social media. The impact of delight in helping other people via web-based networking media utilization isn’t probably going to be contingent on generalized trust, pro sharing norms, or identification.
H5a: Enjoyment in helping others is positively related to social media usage by knowledge contributors
2.3.6 Self-development and use of social media
Self-viability identifies with the impression of individuals about what they can do with the aptitudes they have (Bandura 1986). At the point when individuals share-ability valuable to the association, they pick up trust as far as what they can do and this brings the advantage of expanded self-viability (Constant et al. 1994). This belief can serve as a self-motivational force for knowledge contributors to contribute knowledge to social media (Bock and Kim 2002; Kalman 1999). Knowledge self-efficacy is typically manifested in the form of people believing that their knowledge can help to solve job-related problems (Constant et al. 1996), improve work efficiency (Ba et al. 2001), or make a difference to their organization (Kollock 1999; Wasko and Faraj 2000). On the other hand, if individuals feel that they need learning that is valuable to the organization, they may decay from contributing information to online networking on the grounds that they trust that their commitment can’t have a constructive outcome for the organization The effect of knowledge self-efficacy on social media usage is not likely to be contingent on generalized trust, pro-sharing norms, or identification.

H6: Self-development is positively related to scoial media usage by knowledge contributors or extension professionals.
2.3.7 Subjective norms and social media useA number of studies proposed and proved the direct influence of subjective norms to user’s intention to use a system. The concept of subjective norm (Ajzen, 1991; Fishein ; Ajzen, 1975) is often matched with social influence (Venkatesh, et al., 2003) and social norms CITATION Tho91 l 1033 (Thompson, Higgins, ; Howell, 1991). However, the notion of all the constructs refers to the individual’s behavior that is influenced by the way he believes other view them as a result of using a system (Venkatesh, et al., 2003, p.451). Despite many studies reported the effect of subjective norms to system use is non-significant in voluntary work setting and only significant in mandatory work setting, this study assumed subject norms might have influence over extension professionals use of social media for their work purpose. Hene, it was proposed:
H7: The greater the subjective norm to share knowledge is, the greater the intention to share knowledge will be.

2.3.8 Control variablesAge may be an essential sign as far as utilizing correspondence media, especially for new media like Facebook, twitter, E-mail etc. Earlier investigations have proposed blended discoveries about the connection amongst age and utilization of media. Bhuiyan (1988) and Nuruzzaman (2003) contend that with the expansion of age, people’s slant to attempt new things diminish. The vast majority of the research discoveries on age and utilization of social media demonstrated that they either were of free or had negative relationships. This means that age of the respondents do not possess any significant influence on their social media use to seek and delivery information to others. Besides age, the direct effect of service experience to system use in work setting is rarely studied yet proposed as a moderator (e.g., Venkatesh, et al., 2003). Nonetheless, age and service experience were not considered as predictor variables of ICT use but as control variables (Fig. 2.1).

CHAPTER IIIMETHODOLOGYThis chapter portrays the methodology and techniques utilized as a part of this study. This part is isolated into three areas. The primary area portrays the diagram of research outline. The second area depicts the measurement of variables. At long last, the third area depicts the strategies applied in data analysis
3.1 Research Design
3.1.1 Locale of the studyComilla region was purposively chosen as the investigation territory in any event for two reasons. To start with, the financial and cultivating state of this region was notable to the scientist. Second, he had a decent access to the potential respondents. Comilla has seventeen Upazilas. Nonetheless, considering the time and spending impediment five Upazilas, in particular, Bramanpara, Comilla Sadar, Debidwar, Chandina and Burichong were arbitrarily chosen as the district of the study.

3.1.2 Population and sampling frameAs the study worry about utilization of social media by the extension professionals’ in agricultural knowledge sharing, in a perfect world all the Upazila level extension workers could be constitute the number of inhabitants in this study. However, as SAAOs are the experts who specifically meet and exchange advancements to the ranchers, this study purposely thought about them as the number of inhabitants in this study. But both UAOs and AEOs are also included as respondent. Therefore, all the SAAOs, AEOs and UAOs in the selected five upazilas were constituted the population of the study. The list of all the SAAOs, AEOs and UAOs of the selected upazilas were collected. Thus, a total of 131 SAAOs, 15 AEOs and 5 UAOs were constituted the population of this study (Table 3.1). Among them, five respondents were randomly selected for pre-test. The rest of the SAAOs (i.e., 126 persons) were considered as the sample of this study. All the respondents were informed beforehand to collect the data. However, based on their availability during the data collection period (15th February, 2018 to 25th February, 2018), a total of 126 respondents were interviewed.

Table 3. SEQ Table * ARABIC s 1 1 Population and sample of this studyUpazilas Population Sample size Pre-test sample
Bramanpara31 27 3
Comilla Sadar 26 19 0
Debidwar32 29 2
Chandina 29 23 0
Burichong33 28 0
Total 151 126 5
3.1.3 Instrument for data collectionSince the reasons for study were to test the hypotheses and measure the variances, a cross-sectional review strategy was received for this study. Henceforth, data was gathered utilizing an organized meeting plan. Remembering the targets, the study adjusted approved estimation things from earlier investigations, at whatever point conceivable. The beforehand prepared interview schedule was pre-tried and vital adjustments were completed. In most instances, closed form questions were utilized with the exception of target 3(i.e., problems faced by extension professionals to use social media’) an open-shape question was controlled. Approved estimation things of each construct with their literature sources were exhibited in an English version of the interview schedule as joined in the Appendix-A
3.1.4 Variables of the studyFour variables were used for this study:
Dependent variable: is a variable that is the outcome or result or impact of different factors. This variable is frequently known as a measure or result variable. The estimation of the reliant variable relies upon the estimation of alternate factors, that is, autonomous factors. In this study, Exploration of intention to use of social media in agricultural knowledge sharing by extension professionals’ was considered as the reliant variable.
Independent variable: is a variable that the specialist can control over or control to foresee different factors (i.e., dependent variable). Hence, this variable is regularly called as indicator variable or causal variable. In a trial setting, a researcher needs to control the variable or acquaint another variable with see its impact on the needy variable. In this study, seven independent variables were used. These were: reputation, reciprocity, relationship building and communication efficacy (extrinsic motivation) and self-development, enjoyment and subjective norms (intrinsic motivation)
Control variable: is a variable that the researcher does not want to test in a study and therefore she controls its effect on the other variables to be studied. Here, age, gender and service experience were considered as the control variables.
3.2 Measurement of Variables3.2.1 Measurement of independent variables3.2.1.1 Reciprocity
The reciprocity score of a respondent was computed on the basis of validated measurement scale of facilitating condition was adopted from Venkatesh, et al., (2003) and a five-point rating scale ranging from ‘strongly disagree’ to ‘strongly agree’ was used to capture respondents’ responses against four statements.

Items Score Assigned
Strongly disagree 1
Disagree 2
Undecided 3
Agree 4
Strongly agree 5
Reciprocity score was determined by summing the scores of all the four statements. Thus, the score could range from 1 to 5, where 1 indicated the lesser level of agreement and 5 indicated the higher level of agreement.

3.2.1.2 Reputation
Scales of reputation was adapted from Hossain, et al. (2011). Reputation was captured by using a 5-point rating scale ranging from ‘strongly disagree’ to ‘strongly agree’.

Items Score Assigned
Strongly disagree 1
Disagree 2
Undecided 3
Agree 4
Strongly agree 5
Reputation score was determined by summing the scores of all the four statements. Thus, the score could range from 1 to 5, where 1 indicated the lesser level of agreement and 5 indicated the higher level of agreement
3.2.1.3 Relationship Building
Perceived ease of use refers to the extent to which a respondent perceive use of ICTs would require less effort. The measurement items of this scale were adopted from Davis (1989). Respondents’ responses were captured by a 5-point rating scale ranging from ‘strongly agree’ to ‘strongly disagree’ as follows against four statements.
Items Score Assigned
Strongly disagree 1
Disagree 2
Undecided 3
Agree 4
Strongly agree 5
Ease of use score was determined by summing the scores of all the four items. Thus, the score could range from 4 to 20, where ‘4’ indicates strongly disagreement and ’20’ indicates strongly agreement.
3.2.1.4 Communication efficacy
Communication efficacy was measured by a respondent’s level of confidence to accomplish a job task by performing selected four operations. The modified version of communication-efficacy scales (Compeau ; Higgins, 1995) was used for this instance. The respondents’ responses were captured by using a five-point rating scale ranging ‘strongly agree’ to ‘strongly disagree’ as follows against four statements:
Items Score Assigned
Strongly disagree 1
Disagree 2
Undecided 3
Agree 4
Strongly agree 5
3.2.1.5 Enjoyment
Scales of enjoyment was adopted from Ajzen (1991). Responses were captured using a 5-point rating scale ranging from ‘strongly disagree’ to ‘strongly agree’ which is shown as follows:
Items Score Assigned
Strongly disagree 1
Disagree 2
Undecided 3
Agree 4
Strongly agree 5
The enjoyment score was dictated by summing the scores of all the 4 things. The score in this way could extend from 4 to 20, where ‘4’ shows no impact of enjoyment and ’20’ demonstrates high impact of delight to their utilization of social media in sharing their knowledge
3.2.1.6 Self development
Scales of Self-development support was adapted from Hossain, et al. (2011). Self development was captured by using a 5-point rating scale ranging from ‘strongly disagree’ to ‘strongly agree’.

Items Score Assigned
Strongly disagree 1
Disagree 2
Undecided 3
Agree 4
Strongly agree 5
The self-development support score was determined by summing the scores of all the 4 statements. The self-development score could range from 4 to 20, where ‘4’ indicates low level self-development and ’20’ indicates high level self-development.

3.2.1.7 Subjective norms
Scales of subjective norms were adopted from Ajzen (1991). Responses were captured using a 5-point rating scale ranging from ‘strongly disagree’ to ‘strongly agree’ which is shown as follows:
Items Score Assigned
Strongly disagree 1
Disagree 2
Undecided 3
Agree 4
Strongly agree 5
The subjective norm score was determined by summing the scores of all the 4 items. The score thus could range from 4 to 20, where ‘4’ indicates no influence of subjective norms and ’20’ indicates high influence of subjective norms to their use of ICTs in developing their capacity.

3.2.1.8 Extent of social media use
Extent of social media use refers to the frequency of using social media for accomplishment of a task. The respondents’ responses were captured as follows:
Items Extent of Use Score
Read others’ posts only Frequently (2-3times/ week)
Often (1time/week)
Occasionally (4-5 times/ month)
Rarely (1time/ month)
Not at all (No use) 4
3
2
1
0
Read and share others’ post only Frequently(2-3times/ week)
Often (1time/week)
Occasionally (4-5times/ month)
Rarely (1time/ month)
Not at all (No use) 4
3
2
1
0
Comment on others’ posts only Frequently (2-3times/ week)
Often (1time/week)
Occasionally (4-5 times/ month)
Rarely (1time/ month)
Not at all (No use) 4
3
2
1
0
Post new information related to my work Frequently (1-2 times/day)
Often (1-3 times/week)
Occasionally (5-6 times/month)
Rarely (1-3 times/month
Not at all (No use) 4
3
2
1
0
Post photos and videos Frequently (1-2 times/day)
Often (1-3 times/week)
Occasionally (5-6 times/month)
Rarely (1-3 times/month
Not at all (No use) 4
3
2
1
0
Extent of social media use score was determined by summing the scores of all the 4 items. Thus, it could range from 0 to 16. Where ‘0’means no use of social media and ’16’ means frequently use of social media.
3.2.2 Measurement of dependent variableIntention to use social media by the agricultural extension professionals was measured on the basis of opinion provided by the respondents. Based on the operationalization of the construct, a scale was developed comprised of three statements. The respondents’ responses were captured using a 5-point scale (1-5) ranging from ‘strongly disagree’ to ‘strongly agree’.
Items Score Assigned
Strongly disagree 1
Disagree 2
Undecided 3
Agree 4
Strongly agree 5
The intention to use social media score of a respondent was obtained by adding the scores and it could range from 3 to 15, where ‘3’ indicates no intention to use social media and ’15’ indicates high intention to use social media.
3.3 Data Analysis3.3.1 EditingRaw data were properly reviewed for omitting errors. The researcher made a careful scrutiny when she completed an interview so that all data were included to facilitate coding and tabulation.
Raw data were appropriately explored for omitting errors. The researcher made a watchful scrutiny when he finished a meeting with the goal that all data were incorporated to encourage coding and tabulation.

3.3.2 Coding and tabulationThe researcher consulted with the research supervisor and co-supervisor, made a detailed coding plan. All responses were given in numerical score. The respondent responses were transferred to a master sheet to facilitate tabulation. In accordance with the objectives of the research, all of the data were tabulated.

3.3.3 Categorization of dataFor coding operation, the collected data were classified into various categories. These categories were developed for each of the variables. The percentile function of SPSS software v.23 was used to categorize the variables. The procedure and categorization of a particular variable were further discussed in the chapter 4 in detail.

3.3.4 Method of data analysisData analysis required two stages. To begin with, validation stage and second, result stage. The validation stage sets up the unwavering quality and legitimacy of the measurement items. Four tests need to be carried out to test the reliability and validity of the measurement model, internal consistency (composite reliability), convergent validity (average variance extracted), and discriminant validity and indicator reliability (Hair, et al., 2014). Internal consistency is the value of Cronbach’s alpha which assumes that all the indicators have equal outer loading on the relative constructs. It is expected that the outer loading for each indicator should be above 0.7. However, considering the explorative nature as well as the context, value equal to or greater than 0.65 was considered as accepted. Internal consistency can also be measured by observing the value (0.60-0.70) of composite reliability of a latent variable.Convergenet validity shows whether the indicator can converge or share a high proportion of the variation of the constructs. Average Variance Extracted (AVE) is the common measure of convergent validity which is the grand mean of the squared loadings of a construct’s indicators. A value greater than 0.50 is regarded as a satisfactory AVE score, which says that the construct explains more than half of the variance of its indicators.
Discriminant validity shows the distinctiveness of one construct from others and this can be examined by the cross-loadings of the indicators. If the outer loadings of one indicator on the respective construct are higher than all of its loadings on other constructs assure that the construct has no discriminant validity problem. On the other hand, for indicator reliability, a bootstrapping (a test that relies on random sampling with replacement) procedure needs to be performed. If it shows that the indicator’s weight is statistically significant, then the indicator should be retained otherwise should be removed from the model.
To validate the measurement items and test the structural model, Partial Least Squares (PLS)-based Structural Equation Modeling (SEM) was used for this study (Hair, et al., 2014). Two factors were considered when selecting this modeling approach over traditional statistical tools like SPSS (Statistical Package for Social Sciences). First, PLS-SEM is regarded as a second generation statistical tool over the first generation tool like SPSS and therefore highly accepted to behavioral scientists and academics. Second, tool like SPSS is limited in its ability to measure multi-level path model. As the theoretical model of this study consists of six independent variables, one mediator variable, one dependent variable and two control variables, the confounding effect of one variable on other variables cannot be captured by SPSS and hence, SmartPLS v.2 software application was used to test the model of this study.
Five (5%) percent level of significance was used to test the significance level of each hypothesis. If the computed value of (?) was equal to or greater than the designated level of significance, than the hypothesis was supported and it was concluded that there was a significant contribution of the independent variables to the dependent variable. And if the computed value of (?) is smaller than the designated level of significance than the hypotheses was not supported. Therefore, it assumes that there was no significant contribution of the independent variables to the dependent variable. The results of the reliability and validity tests were given in Chapter Five.

CHAPTER IVRESULTS AND DISCUSSIONThis part displays the aftereffects of this investigation into five areas. To start with, chose attributes of the sample and a clear measurement of this study are introduced. Second, sample’s circulation in light of their watched scores under each measurement is exhibited. Third, reliability and validity of the measurement items took after by consequences of the organized model are given. Finally, extension professionals’ problems concerning social media use in agricultural knowledge sharing is discussed.
4.1 Respondent’s Characteristics and Descriptive StatisticsIn this section the respondent’s characteristics and descriptive statistics are presented in Table 4.1 and Table 4.2. Variables were categorize on the basis of the possible score and age was categorize based on the classification of Ministry of Youth and Sports Governments of the People’s Republic of Bangladesh. Table 4. SEQ Table * ARABIC s 1 1 Respondent’s characteristics (N=126)CharacteristicsFrequencyPercentObserved RangeMeanStandard DeviationGenderMale103 81.7 Female2318.3 Age (in years)Young (up to 35)37 29.4 25-58 43.10 10.487
Middle (36-50)45 35.7 Old (>50)44 34.9 Service experience (in years)Short (up to 10)38 30.2 2-38 20.00 11.587
Medium (11-20)28 22.2 Long (>20)60 47.6 Table 4. SEQ Table * ARABIC s 1 2 Descriptive statistics of constructs used in this studyConstructs Possible range Observed range Mean Standard deviation
Min Max Reciprocity 4-20 12 20 16.62 1.837
Reputation 5-25 17 31 20.71 2.000
Relationship Building 4-20 13 20 17.36 1.723
Communication efficacy 4-20 14 20 16.88 1.372
Enjoyment 4-20 8 19 16.29 1.645
Self-development 4-20 12 20 16.57 1.428
Subjective Norms 4-20 13 20 16.40 1.227
Use of social media 0-25 4 20 13.92 4.059
Intention to use social media 3-15 9 15 13.63 1.563
Table 4.1 reveals that majority of the respondents (81.7%) were male and less than one-fifth (18.3%) were female. The mean of the respondents’ age was 43.10 years with a standard deviation of 10.487. Based on the classification provided by the Ministry of Youth and Sports-Government of the People’s Republic of Bangladesh, almost equal proportion of the respondents (29.4 and 34.9 percent) were young and old aged while around rest of them (35.7 percent) were middle aged. Distribution of the respondents according to their length of service were found almost identical with their age distribution with a mean of 20.00 years. The highest proportions (47.6 percent) of the respondents had long service experience while 30.2 percent had short and 22.2 percent had medium service experience.
4.2 Respondent’s Distribution based on the Salient Factors of extension Professionals’ intention to use social media.

Respondents’ distribution based on the observed scores of the salient factors of professionals’ capacity building through social media is presented in this section.
4.2.1 Reciprocity
The observed reciprocity of individuals’ score of the respondent’s ranged from 12 to 20. The average reciprocity of individuals’ score was 16.62 and the standard deviation was 1.837. Based on the possible range of reciprocity of individuals’ score (4-20), the respondents were classified into following three categories as shown in Table 4.3.

Table 4. SEQ Table * ARABIC s 1 3 Distribution of the respondents according to reciprocity of individuals’
CategoriesFrequencyPercentMeanStd.

Low (up to 7 score) 0 0 16.62 1.837
Medium (8-14 score) 23 18.3 High (;14 score) 103 81.7 Total 126 100Data in Table 4.3 revealed that around half of the respondents (48.1 percent) had low reciprocity of individuals’ where less than one-fourth (18.3 percent) of them had medium and more than three-fourth (81.7 percent) of them had high reciprocity of individuals’. The findings also revealed that an overwhelming matter (0%) of the respondents had low reciprocity. It was noticed in this study that all the respondents had reciprocity behavior.

4.2.2 Reputation
The observed reputation scores of the SAAOs/AEOs/UAOs ranged from 17-31. The average self-efficacy was 20.10 and the standard deviation was 8.362. The respondents were classified into following three categories based on their possible range of reputation score (5-25) as shown in Table 4.4.

Table 4. SEQ Table * ARABIC s 1 4 Distribution of the respondents according to their reputation
Categories Frequency Percent Mean Std.

Low (up to 8 score) 0 0 20.71 2.000
Medium (9-15 score) 0 0 High (;15 score) 126 100 total 126 100 Data in the Table 4.4 show that the highest (100%) percentage of the respondents had high believe that using social media in knowledge sharing increase their reputation.

4.2.3 Relationship building
The observed relationship building scores of the respondents ranged from 13-20 with a mean of 17.36 and standard deviation of 1.723. The respondents were classified into following three categories based on the possible range of perceived ease of use (4-20) as shown in the Table 4.5.
Table 4. SEQ Table * ARABIC s 1 5 Distribution of the respondents according to their perceived ease of useCategoriesFrequencyPercentMeanStd.

Low (up to 7 score)0 0 17.36 1.723
Medium (8-14 score)6 4.8 High (;14 score)120 95.2 Total126 100Data in Table 4.5 reveals that only (4.8 percent) of the respondents using social media as easy compared to the highest (95.2 percent) of the respondents using social media for relationship building. Therefore, it can be concluded that the level of using social media by extension professionals in knowledge sharing was satisfactory.
4.2.4 Communication Efficacy
The observed Communication Efficacy scores of the respondents ranged from 14-20 with a mean of 16.88 and the standard deviation of 1.372. The respondents were classified into following three categories based on the possible range of facilitating condition (4-20) as shown in Table 4.6.
Table 4. SEQ Table * ARABIC s 1 6 Distribution of the respondents according to Communication Efficacy
CategoriesFrequencyPercentMeanStd.

Low (up to 7 score)0 0 16.88 1.372
Medium (8-14 score)4 3.2 High (;14 score)122 96.8 Total126 100 Table 4.6 indicates that majority of the respondents (96.8 percent) having high communication efficacy compared to 4 percent and 0 percent had medium and low communication efficacy, respectively.

4.2.5 Enjoyment
The observed enjoyment scores of the respondents ranged from 8-19 against the possible range of 4-20. The average score was 16.29 and the standard deviation was 1.645. The respondents were classified into following two categories based on their Top management support in the Table 4.8.

Table 4.8 Distribution of the respondents according to their level of enjoyment
CategoriesFrequencyPercentMeanStd.

Medium (8-14 score)6 4.8 16.29 1.645
High (;14 score)120 95.2 Total126 100Data in Table 4.8 reveals that only (4.8 percent) of the respondents using social media as easy compared to the highest (95.2 percent) of the respondents using social media for their personal enjoyment. Therefore, it can be concluded that the level of using social media by extension professionals in knowledge sharing was satisfactory.
4.2.6 Self-development
CategoriesFrequencyPercentMeanStd.

Medium (8-14 score) 4 3.2 16.27 1.428
High (;14 score) 122 96.8 Total 126 100The observed extent of Self-development scores of the respondents ranged from 12-20 against a possible scores of 4-20. The average of self-development score was 16.57 with a standard deviation of 1.428. The respondents were classified into following three categories based on their self-development behavior score as shown in Table 4.9. Table 4. SEQ Table * ARABIC s 1 9 Distribution of the respondents according to their Self-development Table 4.9 indicates that majority of the respondents (96.8 percent) having high believe compared to rest of respondent (3.2 percent) had medium believe that use of social media for their self-development.

4.2.7 Subjective normsThe observed scores of subjective norms of the respondents ranged from 13-20 against the possible range of 4-20. The mean was 16.40 with a standard deviation of 1.227. The respondents were classified into following two categories based on their subjective norms score as shown in Table 4.7.
Table 4.10 Distribution of the respondents according to subjective normsCategoriesFrequencyPercentMeanStd.

Medium (8-14 score)7 5.6 16.40 1.227
High (;14 score)119 94.4 Total131100Data in Table 4.7 shows that the highest proportion (94.4 percent) of the respondents possessed high subjective norms in using social media for job tasks while only 5.6 percent of the respondents possessed medium peer influence and none of them possessed low peer influence. Therefore, it can be said that respondents’ social media use behavior for accomplishing a task was highly influenced by their peers’ influence.
4.2.8 Use of Social media
The observed use of social media scores of the respondents ranged from 4-20 with a mean of 13.92 and the standard deviation of 4.059. The respondents were classified into following three categories based on their possible range (0-25) of use of social media scores as shown in Table 4.11.

Table 4.11 Distribution of the respondents according to their extent of use of social media:
Categories Frequency Percent Mean Std.

Low (up to 7 score) 12 9.5 16.40 1.227
Medium (8-14 score) 68 54.0 High (;14 score) 46 36.5 Total 126 100 Data in table 4.11 show that a majority (54.0 percent) of the respondents were perceived that effective using of social media helped in knowledge sharing while only 36.5 percent of the respondents perceived that effective using of social media helped in medium level and the only 9.5 percent of respondent claim having low benefit.. Majority (54.0 percent) of the extension personnel involved in the study appreciated the advantages using of social media in agricultural extension services.

4.2.9 Intention to use social media
The observed intention use of social media scores of the respondents ranged from 9-15 with a mean of 13.63 and the standard deviation of 1.563. The respondents were classified into following three categories based on their possible range (3-15) of use of social media scores as shown in Table 4.12.

Table 4.12 Distribution of the respondents according to their extent of use of social media:
Categories Frequency Percent Mean Std.

Medium (8-14 score) 4 3.2 13.63 1.563
High (;14 score) 122 96.8 Total 126 100 Data in table 4.12 show that a majority (96.8 percent) of the respondents intended to use social media in agricultural knowledge sharing while only 3.2 percent of the respondents intended to use social media in agricultural knowledge sharing at medium level. Majority (96.8 percent) of the extension personnel involved in the study appreciated the advantages using of social media in agricultural extension services and intended to use it.

4.4 Results of the Structural ModelThe purpose of this section was to examine the effect of seven selected factors on exploration of intention to use social media by extension professionals’ in agricultural knowledge sharing. Multiple regression analysis was used to test the contribution of the selected variables like reciprocity, reputation, relationship building, communication efficacy, enjoyment, self-development, subjective norms and use of social media in agricultural knowledge sharing. Five percent (5%) level of significance were used as the basis for rejection of a hypothesis. A summary of the propose hypotheses is presented in Table 4.12.
Table 4.12 Multiple regression coefficients of the selected factors indicating contribution on intention to use social media in agricultural knowledge sharing
Independent Variables Unstandardized Coefficients Standardized Coefficients t Sig. R2 F
B Std. Error Beta Constant .392 2.220 .177 .860 .291 6.902***
Reciprocity -.143 .075 -.168 NS -1.914 .058 Reputation .156 .073 .199 2.139 .034 Relationship Building .179 .080 .197 2.223 .028 Communication efficacy .237 .114 .208 2.081 .040 Enjoyment .317 .094 .333 3.375 .001 Self-development -.259 .141 -.237 NS -1.839 .068 Subjective Norms .270 .112 .212 2.416 .017 Dependent Variable: Intention to use social media
NSNon-significant
*** Significant at .1% level of significance
** Significant at 1% level of significance
Table 4.13 Summary of the proposed hypothesesNo Hypothesis Supported
H1 Reciprocity is positively related to social media usage by knowledge contributors under conditions of weak pro-sharing norms. No
H2 With the increase of the extent of social media use by extension professionals, their reputation in the organization is increased. Yes
H3 The greater the anticipated reciprocal relationships are, the more favorable the attitude toward knowledge sharing through social media Yes
H4 The higher the individual’s Communication efficacy, the higher the use of Social media. Yes
H5 Enjoyment in helping others is positively related to social media usage by knowledge contributors. Yes
H6 Self-development is positively related to scoial media usage by knowledge contributors or extension professionals No
H7 Extension professionals’ use of social media in agricultural knowledge sharing is positively influenced by subjective norms of using social media. Yes
4.4.1 Discussion of the research findingsA sum of seven hypotheses was proposed in this investigation, of which five speculations were bolstered. This segment gives the talk of the key discoveries as takes after:
4.4.1.1 The Contribution of reputation in using social media
Extent of reputation use was found to be significant predictor of using social media in agricultural knowledge sharing (Table 4.12) which constitute 19.9% of the variance. The relationship between these two constructs was also supported by respondents’ responses on reputation building by the use of social media. Data in descriptive analysis reported that a majority (100%) of the respondents’ social media use as a highly effective medium for knowledge sharing.

4.4.1.2 The Contribution of relationship building in using social media
Relationship building was observed to be the critical benefactor of utilizing social media in agricultural information sharing (Table 4.12) which constitute 19.7% of the variance by extension professionals. Relationship building indicates respondent’s interest in using various social media. An individual with high level of personal thinking in utilizing different social media platform enable them to build up a good relation with others by information sharing.

4.4.1.3 Contribution of communication efficacy in using social media
Communication efficacy was found to be the second highest contributor of the extent of social media use by extension professionals (?=0.208). Communication efficacy indicates respondent’s confident in using various social media tasks. A person with high level of trust in working diverse task via social media empowers them to develop more want for different employments of web-based social networking contrasted with a man with low trust in utilizing online networking.

4.4.1.4 The Contribution of enjoyment in utilizing social media
Enjoyment was found to be the third highest contributor of the extent of social media use by extension professionals to share information (?=0.333, p<0.01). The structural linkage between enjoyment and user’s intention to use social media has been tested in many instances. The auxiliary linkage amongst enjoyment and client’s aim to utilize social media has been tried in numerous cases. That is, enjoyment is an essential property of a framework without which client may plentiful the framework to be utilized. At the point when a man finds a framework simple to utilize empower him to utilize the instrument more. Enjoyment is related to the degree of simplicity associated with the use of social media. Another conceivable clarification of this relationship could be on account of the extension officers were grasping web-based social networking, not from a required setting so far DAE has not made it obligatory to use for their occupations. It is therefore concluded that as extension professionals find a common interest or enjoyment to use that positively impact their use of social media for agricultural knowledge sharing
4.4.1.5 The Contribution of subjective norms in utilizing social media
Subjective norms was observed to be a significant factor of utilizing social media in agricultural information sharing (Table 4.12) which constitute 21.2% of the variance.

Regardless of descriptive statistics of this study uncovered that reciprocity and self-improvement were observed to be seen exceedingly powerful for extension workers to utilize online networking (social media) more for their jobs, the way study did not demonstrate any measurably huge relationship among the concerned factors. This might be caused due to the stronger effects of other predictors such as enjoyment, communication efficacy, and reputation. Therefore, further investigation would be necessary to test the generalizability of this finding.
CHAPTER VSUMMARY, CONCLUSION AND RECOMMENDATIONThe overarching aim of this study was to understand the influence of intention level in social media use by extension professionals to share agriculture related information. The study adopted a theoretical approach and based on ‘Social Exchange Theory’ (Thibaut, et al., 1959) incorporating with the concept of social media usage. According to the ‘Social Exchange Theory’ (Thibaut, et al., 1959) participants in virtual communities expect mutual reciprocity that justifies their expenses in terms of time and effort spent sharing (intrinsic motivation) their knowledge. Through close social interactions, extension workers are able to increase the depth, breadth, and efficiency of mutual knowledge exchange. This study proposed a model which depicts extension professionals’ intention to use of social media which further contingent upon seven independent factors. Data were collected using a cross-sectional survey methodology and analyzed by PLS-SEM using SmartPLS v2.0. In this chapter, the summary of this study is presented.

5.1 Summary of the FindingsThe major findings of the study are summarized below:
5.1.1 Selected factors influencing the extent of social media use5.1.1.1 Reciprocity
Nearly below, one-fourth of the respondent (18.3 percent) had medium reciprocity where above three-fourth (81.7 percent) had high level of reciprocity. It was observed that all the respondents had a high intention to use social media.

5.1.1.2 Reputation
All of the respondents (100 percent) had high reputation building intention by using social media in the purpose of knowledge sharing. It was observed that every professionals’ of this study fully aware about how using social media increase their reputation in the associated organization.

5.1.1.3 Relationship building
Just 4.8 percent of the aggregate respondents of this investigation trust that a decent relationship can be develop among the experts by utilizing social media in agricultural information transferring. On the other, a dominant part rate (95.2%) of respondent emphatically trust that a decent relationship can be develop among the experts by utilizing web-based social networking in agricultural information transferring.
5.1.1.4 Communication efficacy
Below one-tenth of the total respondents (3.2 percent) perceived medium followed by 96.8 percent perceived high believe that using social media has a vital importance in increase of communication efficacy.

5.1.1.5 Enjoyment
The highest proportion (95.2 percent) of the respondents possessed high level of belief that they use social media as for their personal interest or enjoyment whereas only 4.8 percent of the respondents possessed medium level of belief that they use social media as for their personal interest to meet up job related queries.
5.1.1.6 Self-development
The most elevated extent (96.8 percent) of the respondents had high state of conviction that they utilize web-based social networking to accelerate the procedure of self-improvement while just 3.2 percent of the respondents had a medium level of conviction that they utilize online networking to accelerate the procedure of self-development
5.1.1.7 Subjective Norms
The most noteworthy extent (94.4 percent) of the respondents had high companion impact and just 5.6 percent of the respondents had a medium associate impact for their utilization of online networking for work-related purposes. The finding demonstrates every one of the respondents was impacted by their companion bunches in utilizing online networking for achieving work errands.

5.1.1.8 Use of social media
A vast number of the respondents (54.0 percent) perceived that effective using of social media moderately helped them in capacity building while 36.5 percent perceived that social media’ effects were high in sharing knowledge. The lowest number of respondent (9.5 percent) of the extension personnel involved in the study appreciated the advantages of social media usage in their job purposes.

5.1.1.9 Intention to use social media
Countless respondents (96.8 percent) trust that powerful utilization of social media exceedingly helped them in expanding their own aptitude in their related activity field while just 3.2 percent say that utilizing of web-based social networking decently helped them in expanding their own expertise. For why one might say that Majority (96.8 percent) of the expansion workforce proposed to keep proceed with the utilization of web-based social networking in agricultural information sharing.

5.1.2 Results of the theoretical modelThere were seven hypotheses were proposed in the model. Five (5), out of seven were found to be statistically significant while two hypotheses were found to be unsupported. A summary of the findings of the proposed hypotheses are presented as follows:
5.1.2.1 Problems faced by extension professionals using social media
Problems faced by extension professionals using social media was identified by using a well-known qualitative data analytic tool, ‘thematic analysis’ which revealed five key problems. These were: high cost, lack of time, poor IT infrastructure, and access barrier and lack motivation.

5.2 ConclusionWhile traditional ICTs were the weak ties for diffusion of innovation, modern day ICTs are bringing vast amount of information to rural communities. But among these, social media are unique because of the potential they provide for forming both strong and weak ties in communication. The society – the rural people, the field level Extensionists, farmers – do not read journals; they read blogs, watch YouTube and use Facebook and Twitter and these are the mediums that reach them effectively. These platforms provide incentives to every actor to communicate online forming networks and initiating development. Empowered by mobile technology, social media has a huge potential to revolutionize communication but its success depends, to a large extent, on the innovativeness of AEIS and grass root level organizations. Mobilizing actors in AIS to use social media needs to be addressed first and raising awareness is a big challenge. Moreover, without infrastructure, only information can do very little. Further research into actual impact of social media on rural development and then scaling up are needed at local and global level. Extension is not just about communicating but bringing behavioral change thus mere sharing posts and social media activism is not going to change much without practical actions. A multi-level approach and initiatives at institutional and individual level together is needed to make social media a reality in every sphere of agricultural extension and advisory services.

Discoveries of the present study and the logical interpretation of other significant actualities incited the researcher to reach the accompanying determinations:
Reputation significantly added to the utilization of web-based social networking. In this way, one might say that reputation is one of the critical indicators of the degree of utilizing online networking. Reputation shows the respondents’ conduct to use social media tools. As reputation is an extraneous inspiration, is one of the essential preconditions of web-based social networking utilization. In this way, it can be inferred that higher reputation building goal may prompt higher utilization of online networking which in swings prompt higher information sharing.
Communication efficacy had second highest contribution to the extent of social media use. This facts lead to the conclusion that any arrangement made to increase communication efficacy of the respondents would ultimately increase use of social media in agriculture.

Relationship building had a huge commitment to the degree of utilizing online networking utilization. In this way, it might be inferred that when the extraneous inspiration like relationship building goal increment to impart information to each other the utilization of web-based social networking proportionately increments.

Enjoyment possessed the highest level of significant in the use of social media. In this way, one might say that enjoyment is one of the critical indicators of the degree of utilizing social media. Enjoyment shows the respondents’ conduct to use social media tools. As Enjoyment is an intrinsic inspiration, is one of the essential preconditions of web-based social networking utilization. Therefore, it can be concluded that higher enjoyment may prompt higher utilization of online networking which in swings prompt higher information sharing.
The most noteworthy extent (94.4 percent) of the respondents had high companion impact and just 5.6 percent of the respondents had a medium associate impact for their utilization of online networking for work-related purposes. The finding demonstrates every one of the respondents was impacted by their companion bunches in utilizing online networking for achieving work errands.

5.3 RecommendationsFrom reviews and findings of the survey, it is clear that social media is fast becoming an integral part of agricultural communication and it is being readily accepted as the next big thing in AEIS. Though agricultural organizations are slowly adapting to the changing scenario, faster actions are required to better utilize social media. To overcome the challenges, a multipronged approach is needed at different levels:
5.3.1 Recommendations for Individual level
Extensionists need to take personal initiative to use social media as part of their job within the norms of institutional guidelines. Continuous engagement at individual level is needed for mass influence and to carry out fruitful discussions and encourage rural communities to get involved.

Encouraging extension professionals, agripreneurs, and agribusinesses to directly connect with consumers through social media can raise awareness about agriculture and the same time increase income.

Faster translation of research findings into practical application can be ensured by sharing results through social media among communities of Extensionists and professionals. This can also reduce the gap between research and practice.

As therefore, more usage of social media should be launched to target groups. Number of social media group should also be increased and the contents provided through the social media group should be more relevant and specified. Images and pictures that are provided in the social media group should be clearer.

Recommendations for Organizational level:
Formulation of favorable social media policy and guidelines and coordinated strategies are required. A clear understanding of the audience should be the foremost step to plan a social media strategy.

Encouraging use of social media to promote organizational goals, actions, and success.

Training employees not just at the bottom level but also at higher level of hierarchy to help them understand and use social media appropriately.

Organizing workshops and hands-on-training for clients to create awareness about utility of social media and also developing skill to use it.

Employing social media officer or communication officers to manage social media accounts, create content with experts, and gatekeeping.

Private institutions and development agencies can try crowd-funding development projects through social media to raise awareness and financially sustain the projects.

Organizations need to find innovative ways (like felfies) to promote social media use in agriculture among farming community especially among rural youth and women to make farming attractive.

Recommendations for Infrastructural level:
Basic infrastructure like power supply and access to network services are necessary to access social media.

Markets, road, and transportation need to be created in rural areas for translation of information into practical use.

Free Wi-Fi in public places in rural areas by the government can be helpful in accessing social media.

Recommendations for Policy level:
Regulation of data tariffs in the rural areas and introduction of zero rating services (Bleiberg and West, 2015), by the government can help in making it accessible to the rural people.

Promoting use of social media at the government level can encourage faster adoption.

Major social media awareness campaigns and other such initiatives for increasing social media technical literacy of rural people.

CHAPTER V
REFERENCESAhlqvist, T., Back, A., Halonen, M. and Heinonen, S. 2008. Social media roadmaps: Exploring the futures triggered by social media.

Ajzen, I. (1991). The Theory of Planned Bahavior. Organizational Behavior and Human Decision Processes. 50(2):179-211.

Allen, N. J. and Meyer, J. P. (1990). The measurement and antecedents of affective, continuance and normative commitment to the organization. Journal of occupational psychology, 63 (1), pp. 1–18.

Amy M. Young, Mary D. Hinesly (2014). Social Media Use to Enhance Internal Communication: Course Design for Business Students, Vol 77, Issue 4, pp.426– 439.

Andres, D. and Woodard, J. 2013. Social media handbook for agricultural development practitioners. USAID and FHI 360.

Ba, S., Stallaert, J., and Whinston, A. B. “Research Commentary: Introducing a Third Dimension in Information Systems Design? The Case for Incentive Alignment, “Information Systems Research (12:3), 2001, pp. 225-239
Bandura, A. Social Foundations of Thought and Action: A Social Cognitive Theory, Prentice Hall, Englewood Cliffs, NJ, 1986.
Behringer, N. and Sassenberg, K. (2015) Introducing social media for knowledge management: Determinants of employees’ intentions to adopt new tools, Computers in Human Behavior, vol. 48, pp. 290-296.

Bellefroid, B. (2012) The new way of knowledge sharing a thesis research about the effects of NWOW on knowledge sharing, Online, Available: http://www.cs.uu.nl/education/scripties/pdf.php?SID=INF/SCR-2012-009
Blau, P. Exchange and Power in Social Life, Wiley, New York, 1967.

Blau, P. M. Exchange and Power in Social Life, John Wiley, NewYork, 1964.
Bleiberg, J. and West, D.M. 2015. 3 ways to provide Internet access to the developing world.http://www.brookings.edu/blogs/techtank/posts/2015/03/2-digitaldivide-internet-west (Published on March 02, 2015; Accessed on September 09, 2015).

Bock, G. W., Zmud, R. W., Kim, Y. G., and Lee, J. N. “Behavioral Intention Formation in Knowledge Sharing: Examining the Roles of Extrinsic Motivators, Social-Psychological Forces, and Organizational Climate,” MIS Quarterly (29:1), March 2005, pp. 87-111.

Bresman, H., J. Birkinshaw & R. Nobel. (1999). Knowledge Transfer in International Acquisitions. J. Int’l. Busi. Stud. 30:439 – 462
Cassa, C., R. Chunara, K. Mandl ; J. Brownstein. (2013). Twitter as a Sentinel in Emergency Situations: Lessons from the Boston Marathon Explosions – PLOS Currents Disasters
Cavazza, F., 2010, Social Media Landscape Redux, Accessed November 8, 2010, http://www.fredcavazza.net/2009/04/10/social-media-lands cape-redux/
Choo, C. (1998) The Knowing Organization: How Organizations Use Information for Construct Meaning, Create Knowledge and Make Decisions, Oxford Press, New York
Chunara, R., J. R. Andrews ; J. S. Brownstein. (2012). Social and news media enable estimation of epidemiological patterns early in the 2010 Haitian cholera outbreak. Am. J. Trop. Med. Hyg. 86: 39-45.
Citizenship Behavior,” Journal of Applied Psychology (74:1), 1989, pp. 157-164.Miles, M. B., and Huberman, A. M. Qualitative Data Analysis. Sage Publications, Inc., Thousand Oaks, CA, 1994.

Claudio Castellano, Santo Fortunato, and Vittorio Loreto. Statistical physics of social dynamics. Rev. Mod.Phys., 81(2):591{646, May 2009.

Connolly, T., and Thorn, B. K. “Discretionary Databases: Theory, Data, and Implications,” in Organizations and Communication Technology.

Constant, D., Kiesler, S., and Sproull, L. “What’s Mine Is Ours or Is It? A Study of Attitudes about Information Sharing,” Information Systems Research (5:4), 1994, pp. 400-421.

Constant, D., Kiesler, S., and Sproull, L. “The Kindness of Strangers,” Organization Science (7:2), 1996, pp. 119-135
Constant, D., Sproull, L., and Kiesler, S. “The Kindness of Strangers: The Usefulness of Electronic Weak Ties for Technical Advice,” Organization Science (7:2), 1996, pp. 119-135.

Cummings, J. N. (2004) Work groups, structural diversity, and knowledge sharing in a global organization, Management Science, vol. 50, no. 3, pp 352?364.

Dalkir, K. (2005) Knowledge Management in Theory and Practice. MA: Elsevier, Boston
Davenport, T. H., and Prusak, L. Working Knowledge: How Organizations Manage What They Know, Harvard Business School Press, Boston, 1998.

Davenport, T. H., De Long, D. W., and Beers, M. C. “Successful Knowledge Management Projects,” Sloan Management Review (39:2), 1998, pp. 43-57.Constant, D., Kiesler, S., and Sproull, L. “What’s Mine Is Ours or Is It? A Study of Attitudes about Information Sharing,” Information Systems Research (5:4), 1994, pp. 400-421
Davenport, T. H., De Long, D. W., and Beers, M. C. “Successful Knowledge Management Projects,” Sloan Management Review (39:2), 1998, pp. 43-57.

De Silva, H., & Ratnadiwakara. D. (2008). Using ICT to Reduce Transaction Costs in Agriculture through Better Communication: A Case Study from Sri Lanka. Colombo, SriLanka: LIRNE asia. www.lirneasia.net/wpcontent/uploads/2008/11/transactioncosts.pdf.

‘Dell, C, and Grayson, C. J. “If Only We Knew What We Know: Identification and Transfer of Internal Best Practices,” California Management Review (40:3), 1998, pp. 154-174.

Dennis.E & Merill.J. (2010). Media Debates Great Issues For the Digital Age California: Thomson Wadsworth.

Diekmann, F., C. Loibl, & M. T. Batte. (2009). “The Economics of Agricultural Information: Factors Affecting Commercial Farmers’ Information Strategies in Ohio.” Review of Agricultural Economics 31 (4): 853–872.

Dumbrell, D. and Steele, R. (2014) Social Media Technologies for Achieving Knowledge Management Amongst Older Adult Communities, Procedia – Social and Behavioral Sciences, vol. 147, pp. 229-236.

European Commission (2010) Communication from the Commission Europe 2020: A strategy for smart, sustainable and inclusive growth, Online, Available: http://ec.europa.eu/eu2020/pdf/COMPLET%20EN%20BARROSO%20%20%20007%20-%20Europe%202020%20-%20EN%20version.pdf
Fishbein, M., & Ajzen, I. (1975). Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research. Reading, MA: Addison-Wesley.

Gaál Z., Szabó, L. and Obermayer-Kovács, N. (2014) ‘Personal knowledge sharing: Web 2.0 role through the lens of Generations’, ECKM 2014 – Conference Proceedings, 15th European Conference on Knowledge Management, Santarem, pp. 362?370.

Gaál Z., Szabó, L., Kovács, Z., Obermayer-Kovács, N. and Csepregi A. (2008) ‘Knowledge Management Profile Maturity Model’, ECKM 2008 – Conference Proceedings, 9th European Conference on Knowledge Management, Southampton, pp. 209-216
Gakuru, M; Kristen W. & Stepman, F. (2009). Inventory of Innovative Farmer Advisory Services Using Information Communication Technologies. The Forum for Agricultural Research in Africa.

Gottschalk, P. (2007) CIO and corporate strategic management: changing role of CIO to CEO, Idea Group Publication, Hershey PA
Gray, P. H. (2001) The Impact of Knowledge Repositories on Power and Control in the Workplace, Information Technology and People, vol. 14, no. 4, pp 368-384.

Hall, H. (2001) “Social Exchange for Knowledge Exchange,” paper presented at Managing Knowledge: Conversations and Critiques, University of Leicester Management Centre, April 10-11.

Hall, H. (2001) Social Exchange for Knowledge Exchange, Managing Knowledge: Conversations and Critiques, University of Leicester Management Centre, Online, Available: http://researchrepository.napier.ac.uk/3276/1/hall.pdf
Hansen, M. T., Nohria, N. and Tierney, T. (1999) What is your strategy for managing knowledge, Harvard Business Review, March/ Apr, pp. 106-116.

Heinzelman J, R. Brown, P. Meier. (2011) Mobile Technology, Crowdsourcing and Peace Mapping: New Theory and Applications for Conflict Management. Mobile Technologies for Conflict Management Law, Governance and Technology Series. P. 39-53.
Hemsley, J. and Mason, R.M. 2013 Knowledge and Knowledge Management in the Social Media Age, Journal of Organizational Computing and Electronic Commerce, 23(1-2):138-167. DOI: 10.1080/10919392.2013.748614.

Huysman, M. H. and Wit, D. (2004) Knowledge Sharing in Practice, Dordrecht: Kluwer Academics.

Ipe, M. (2003) Knowledge Sharing in Organizations: A Conceptual Framework, Human Resource Development Review, vol. 2, no. 4, pp. 337-359.

Janz, B.D. and Prasarnphanich, P. (2003) Understanding the antecedents of effective knowledge management: The importance of a knowledge-centered culture, Decision Sciences, vol. 34, no. 2, pp. 351-384.

Kalman, M. E. The Effects of Organizational Commitment and Expected Outcomes on the Motivation to Share Discretionary Information in a Collaborative Database: Communication Dilemmas and Other Serious Games, unpub lished Ph.D. Thesis, University of Southern California, Los Angeles, CA, 1999.

Kaplan, A. M., & Haenlein, M. 2010. Users of the world, unite! The challenges and opportunities of social media. Business Horizons, 53(1), 59-68. doi: 10.1016/j.bushor.2009.09.003.

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.

Kollock, P. “The Economies of Online Coopera tion: Gifts and Public Goods in Cyberspace,” in Communities in Cyberspace, M. Smith and P. Kollock (Eds.), Routledge, New-York, 1999, pp. 220-239.
Kollock, P. “The Economies of Online Coopera tion: Gifts and Public Goods in Cyberspace,” in Communities in Cyberspace, M. Smith and P. Kollock (Eds.), Routledge, NewYork, 1999, pp. 220-239.
Kothari. (2004). Research methodology: Methods and techniques. New Age International.

KPMG (2003) Insights from KPMG’s European Knowledge Management Survey2002/2003. KPMG Consulting Report, Online, Available:ep2010.salzburgresearch.at/ knowledge_base/kpmg_2003.pdf
Krebs, D. L. “Empathy and Altruism,” Journal of Personality and Social Psychology (32:6), 1975, pp. 1132-1146.
Kuria, CW 2014. ‘Use of Social Media as a Source of Agricultural Information by Small Holder Farmers: A Case Study of Lower Kabete Kiambu County (MA Thesis)’ University of Nairobi. Pp 4-5.

Lu, X., L. Bengtsson ; P. Holme. (2012). Predictability of population displacement after the 2010 Haiti earthquake. Proc. Natl. Acad. Sci. 109: 11576-11581.

Mayfield, A. 2008. What is social media? http://www.repromax.com/docs/113/854427515.pdf MEAS. 2015. Modernizing extension
Merriam-Webster. (2015) Social media. Retrieved from https://www.merriam-webster.com/dictionary/social%20media
Michelle Chmielewski (2011), what is social media? https://heidicohen.com/what-is-social-media/
Nahapiet, J., and Ghoshal, S. “Social Capital, Intellectual Capital, and Organizational Advantage,”Academy of Management Review (23:2), 1998, pp. 242 266.
Negroponte, N. (1995) being digital, Alfred A. Knopf, New York
Nonaka, I. and Takeuchi, H. (1995) The Knowledge-creating Company, Oxford University Press, New York
Odero P.W. (2013). The Role of Social Media as a Tool for Peace Building and Conflict Prevention in Kenya, The case of Nairobi County. University of Nairobi, Master Thesis.

Organ, D. W., ; Konovsky, M. (1989). Cognitive versus affective determinants of organizational citizenship behavior. Journal of applied psychology, 74(1), 157
Ovadia, S. (2014). ResearchGate and Academia.edu: Academic social networks. Behavioral and Social Sciences Librarian, 33(3):165-169.

Paroutis and Saleh (2009) Determinants of knowledge sharing using Web 2.0 technologies, Journal of Knowledge Management, vol. 13, no. 4, pp. 52-63.

Polányi, M. (1966) The Tacit Dimension, Routledge ; Kegan Paul, London
Quigley, N. R., Tersluk, P. E., Locke, E. A. and Bartol, K. M. (2007) A multilevel investigation of the motivational mechanisms underlying knowledge sharing and performance, Organization Science, vol. 18, no. 1, pp. 71-88.

Rheingold, H. The Virtual Community: Home steading on the Electronic Frontier, MIT Press, Cambridge, MA, 2000.

Safko L; Brake D.K. (2009). The social media Bible: tactics, tools and strategies for business success. Hoboken, NJ: John Wiley ; Sons.

Saravanan, R. and Bhattacharjee, S. 2014. Social media: New generation tools for agricultural extension? http://www.aesagfras.net/Resources/file/Saravanan%20Final%20blog%2042.pdf
Saravanan, R., Suchiradipta, B., Chowdhury, A., Hall, K. ; Odame, H. H. 2015. Social Media for Rural Advisory Services, Note 15. GFRAS Good Practice Notes for Extension and Advisory Services. GFRAS: Lindau, Switzerland. www.betterextension.org
Sigalaa, M. and Chalkiti, K. (2015) Knowledge management, social media and employee creativity, International Journal of Hospitality Management, vol. 45, pp. 44–58.

Simonson, J. 2013. Top 5 reasons to use LinkedIn foragvocacy. http://jordansimonson.wordpress.com/2013/05/21/ top-5-reasons-to-use-linkedin-foragvocacy/ (Posted on 21.05.2014; Accessed on 26.11.2014).

Smith, D. H. “Altruism, Volunteers, and Volunteerism,” Journal of Voluntary Action Research (10:1), 1981, pp. 21-36.

Tang, Q., Gu, B., ; Whinston, A. B. (2012). Content contribution for revenue sharing and reputation in social media: A dynamic structural model. Journal of Management Information Systems, 29(2), 41-76.

Terry, M. 2009. Twittering healthcare: Social media and medicine. Telemedicine and e-Health, 15, 507-510. doi: 10.1089/tmj.2009.995.

Thibaut, J. W., H. H. Kelly. (1959).The Social Psychology of Groups, John Wiley ; Sons, New York.

Thompson, R. L., Higgins, C. A., ; Howell, J. M. (1991). Personal Computing: Toward a Conceptual Model of Utilization. MIS Quarterly. 15(1):124-143.

Venkatesh, V., Morris, M. G., Davis, G. B., ; Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. MIS Quarterly. 27(3):425-478.

Wasko, M. M., and Faraj, S. “It Is What One Does’: Why People Participate and Help Others in Electronic Communities of Practice,” Journal of Strategic Information Systems (9:2/3), 2000, pp. 155-173.

APPENDIX- AEnglish Version of the Interview Schedule
Department of Agricultural Extension ; Information System
Sher-e-Bangla Agricultural University
Dhaka-1207
Interview Schedule for data collection for the Research on
Use of Social Media for Agricultural Knowledge Sharing by the Extension Professionals
(This interview schedule is entitled for a research study. Collected data will only be used for research purpose and will be published aggregately)
Serial No
Name of the respondent
Designation
Upazila District
Age: Please mention your current age _____(years)
Gender: i) Male ii) Female
Service Experience: How long have you been working in the Extension Service ________ (years
Reciprocity (Kankanhalli, et al. 2005): Please mention your degree of agreement or disagreement with the following statements.
No. Items Strongly Disagree Disagree Undecided Agree Strongly Agree
1. When I share any information regarding my work on social media, I believe I will receive information from others as well 2. When I respond to someone’s queries for any information on social media, I expect someone also respond me when I am in need of information regarding my work 3. When I help others by providing information through social media, I expect other can also help me when I need it 4. I know that other members will help me so it’s only fair to help other members Reputation (Kankanhalli, et al. 2005): Please mention your degree of agreement or disagreement with the following statements
No. Items Strongly Disagree Disagree Undecided Agree Strongly Agree
1. Sharing knowledge through social media improves my image within the organization 2. I earn respect from others by sharing knowledge through social media 3. I feel that social media participation improves my status in the profession
4. People in the organization who share their knowledge through social media have more prestige than those who do not 5. When I share my knowledge through social media, my colleagues praise me Relationship Building (Bock, et al. 2005): Please mention your degree of agreement or disagreement with the following statements
No. Items? Strongly Disagree Disagree
Undecided Agree Strongly Agree
1. My knowledge sharing would strengthen the ties between existing members in the organization and myself 2. My knowledge sharing would get me well acquainted with new members in the organization 3. My knowledge sharing would expand the scope of my association with other members in the organization 4. My knowledge sharing would create strong relationships with members who have common interests in the organization Communication efficiency: Please mention your degree of agreement or disagreement with the following statements.

No. Items Strongly Disagree Disagree Undecided Agree
Strongly Agree
1. I can easily share my information through social media 2. I can quickly communicate with others about any problem related my work 3. I think it is the most efficient way to communicate with people whom I work with 4. I think it is a less costly medium to communicate Enjoyment (Kankanhalli, et al. 2005): Please mention your degree of agreement or disagreement with the following statements.
No. Items Strongly Disagree Disagree Undecided Agree
Strongly Agree
1. I feel good to share knowledge through social media 2. I enjoy helping others by my sharing knowledge through social media 3. Sharing my knowledge with others through social media give me pleasure 4. It feels good to help someone else by sharing knowledge through social media Self- development (Kankanhalli, et al. 2005): Please mention your degree of agreement or disagreement with the following statements.

No. Items Strongly Disagree Disagree Undecided Agree
Strongly Agree
1. I believe by knowledge sharing increase my efficacy 2. I think my ability to provide knowledge through social media that others in my organization consider valuable 3. I believe I have the expertise needed to provide valuable knowledge for my organization 4. I believe my efficacy in work will be enhanced from others’ information sharing on social media Subjective norms: Please mention your degree of agreement or disagreement with the following statements.

No. Items Strongly Disagree Disagree Undecided Agree Strongly Agree
1. My colleagues think I should use social media 2. My peers think I should use social media 3. People whom I interact with think I should use social media 4. The people I communicate with for my work purpose think I should use social media Use of social media: Please mention how frequently you use social media for sharing of information related to your work.

No Items Not at all Rarely Occasionally Often Frequently
1. Read others’ posts only (No use) (1time/ month) (4-5 times/ month) (1time/week) (2-3times/ week)
2. Read and share others’ post only (No use) (1time/ month) (4-5 times/ month) (1time/week) (2-3times/ week)
3. Comment on others’ posts only (No use) (1time/ month) (4-5 times/ month) (1time/week) (2-3times/ week)
4. Post new information related to my work (No use) (1time/ month) (4-5 times/ month) (1time/week) (2-3times/ week)
5. Post photos and videos (No use) (1time/ month) (4-5 times/ month) (1time/week) (2-3times/ week)
Intention to continue use social media: Please mention your degree of agreement or disagreement with the following statements
No. Items Strongly Disagree Disagree Undecided Agree Strongly Agree
1. I want to continue to share information through social media 2. I will continue to use social media for my work purpose 3. I will increase my use of social media for sharing information related to my work Please mention the problems you faced (at least two) for sharing work related information using social media.

a) b)

c) d)
Thank You
Name ; Signature of the Interviewer:
_______________________________________________