Company’s Image Evaluation in Online Social Networks

Therefore, a case study is proposed in section 3 in order to determine the incidence of the OSN activity and participation on a user’s opinion about a certain company. The grey systems theory will be used in shaping these relations as it has been widely applied in applications involving a high degree of uncertainty.

Grey Analysis

The incidence analysis is a central method in the grey systems theory and it is one of the most employed techniques when dealing with uncertain situations. Over the time, there have been created a series of incidence degree, among which it can be mentioned: the degree of grey B mode incidence [15], the degree of grey C mode incidence [16], the degree of grey T mode incidence [14], the synthetic degree of grey incidence [10], the local degree of grey incidence [18], the Gini degree of grey incidence [11], grey distance incidence degree [9], Deng’s degree of grey incidence [6] etc.
The Deng’s degree of grey incidence will be used in the analysis conducted in section 3 due to its easiness of use and demonstrated practical applicability. Considering the following [6]:

A number of relevant factors sequences for this system, given by:
                                                           X_j=(x_(1,j),x_(2,j),…,x_(t,j))

where: =1,2,…,n , t = the period of time and n = the considered variables   and: x_(k,j)>0,k=1,…,t;
The calculated values of the incidence degree of a relevant factors sequence on its main characteristics will be noted as: γ (X₀,X_j ).

Deng’s degree of grey incidence [6] is calculated as follows:

Case Study

The case study was conducted to a 258 respondents, having the age between 18 and 41 years old. Among them, 98.40% are members on the online social networks, while the rest of have never been a part of this kind of networks, which reduced our sample to 254 valid respondents. Among these, 90.94% have seen a commercial in the social media in the last year or have seen and participated to a discussion related to a company’s product/ service.

It was interesting to know how open the consumers are to the discussions initiated in online social networks and, for this, they have been asked to point out how often they read or actively take part on these discussions. The answers have been structured though a 4 point scale: never, sometimes, often and always and they are: 2.44% never, 26.83% sometimes, 51.22% often and 19.51% always.

Another question was trying to find out if the online social networks users are paying more attention to the online discussion related to the products/ services they are frequently using. The respondents’ answers showed that 82.49% of them are attentive to this kind of information.

Therefore, for shaping the relationship between the OSN and a company’s image, four variables have been considered: company’s image (CI), users’ social influence on OSN (USI), organizational promotion in OSN (OP), perceived image in OSN (PI).

These variables have been measured using a 5-point Likert scale. First of all, the respondents were asked to think about a company whose products/ services are in their interest area and to answer to a series of questions regarding that company and their activity on OSN using a 5-point evaluation scale (1 – strongly disagree; 2 — disagree; 3 – undecided;4 – agree;5 – strongly agree), as in the following [1,2,4,8, 17,19]:

–    Company’s image (CI):
o    Emotional appeal (EA): I have a good opinion about that company;
o    Products and services (PS):
    The company is offering high quality products/services (PS1);
    The company is offering products/ services that are good value for money (PS2).
o    Leadership and vision (LV): The company recognizes and take advantage of market opportunities.
–    Organizational promotion in OSN (OP):
o    Active advertising (AA): The company is actively advertising its products/services in OSN;
o    Active involvement (AI): I am constantly receiving updates and information about that company’s products/services.
–    Users’ social influence on OSN (USI): measured through the number of direct contacts in OSN who have adopted/used the products/services of that company divided by the number of direct contacts that the respondent is having on ONS.

–    Perceived image in OSN (PI):
o    Friends’ opinion (FO): My friends will be impressed if I own/buy that company’s products/ services;
o    Media image (MI): The company gets mainly positive coverage in media;
o    Sense of achievement (SA): I would feel a sense of achievement to having that company’s products/ services

The figure 2 in the following is picturing the considered constructions.

Concluding Remarks

With the appearance and development of the new Web 2.0 technologies, the ONS have become part of our every-day life, being a proper environment for spreading the information and knowledge with people from all around the world.

In this context, the present paper aims to shape the relation between users’ activity in the online environment and their opinion of a company measured through its image. For this, a case study has been employed and a grey incidence analysis has been conducted among the four considered variables. The results have been concluding: the company’s image is related to all three constructions:  the users’ social influence, the organizational promotion and the perceived image in OSN. Among these, the perceive image has the strongest relation with users’ opinion about a company’s image, which can be useful in the impression management process.

As further work, the company’s image and image will be putted into connection with the users’ actual buying decisions, determining to which extent the investment on increasing a firm’s image can have visible and sustainable effects on its sales.

Acknowledgments

This paper was cofinanced from the European Social Fund through Sectorial Operational Programme Human Resources Development 2007-2013, project number POSDRU/159/1.5/S/134197 „Performance and excellence in doctoral and postdoctoral research in Romanian economics science domain” Also, this work was co-financed from the European Social Fund, through the Sectorial Operational Programme Human Resources Development 2007-2013, project number POSDRU/159/1.5/S/138907 “Excellence in scientific interdisciplinary research, doctoral and postdoctoral, in the economic, social and medical fields -EXCELIS”, coordinator The Bucharest University of Economic Studies. Moreover, the authors gratefully acknowledge partial support of this research by Webster University Thailand.

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