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Original Article | Open Access | Can. J. Bus. Inf. Stud., 2022; 4(5), 112-124 | doi: 10.34104/cjbis.022.01120124

Factors Affecting Users Intention to Use Social Networking Sites: A Mediating Role of Social Networking Satisfaction

S. M. Ashraful Alam Mail Img ,
Mohammad Rakibul Islam Bhuiyan Mail Img ,
Somaya Tabassum Mail Img ,
Md. Tariqul Islam Mail Img

Abstract

This research is aimed to identify factors affecting users Intention to Use (ITU) Social Networking Sites (SNSs) with moderating role of social networking satisfaction. There are considerable research works regarding factors influencing the Intention to Use (ITU) Social Networking Sites (SNSs), but no research is conducted on a mediating factor of social networking satisfaction. This research intends to identify the relation of sociability, fashion/ status, perceived entertainment, and perceived benefit with social networking satisfaction and identify the degree to which social networking satisfaction is associated with using SNSs. For this purpose, three hundred eleven data were collected by online survey and in-person interviews from Dhaka city. After that, we analyzed data by smart PLS-SEM. We justified the measurement model to determine whether constructs represent users ITUSNSs. When data validation was confirmed, we analyzed the structural model by smart PLS 3.3.3. From our analysis, it is revealed that social networking satisfaction partially mediates sociability motivation, fashion/status, and perceived benefit, whereas it completely mediates perceived entertainment. This result will help the practitioners to make decisions on users social networking satisfaction. Because this factor partially or completely mediates the other factors influencing users ITUSNSs. There are some limitations to this research. Future researchers should take more sample sizes and consider all age-ranged respondents. They can also conduct the same research based on a different model to justify the present study. They may also take another or multiple mediating variables for this study. 

INTRODUCTION

In this fourth industrial revelation age, SNSs play a great role in communication, idea sharing, advertisement, marketing, enjoyment, and so forth (Salleh et al., 2013). There various SNSs like Facebook, Twitter, My-space, Google+, etc. All of these are essential parts of our lives. Registration is required to get an account on those platforms and make a profile of an individual to disseminate information and to be appeared to different groups (Hew, 2011). After logging in, the users can post, share, comment, like/dislike, and do many more things. SNSs are a popular and common platform for online social exchange of thoughts and for sharing feelings (Hoadley et al., 2010; Parvez et al., 2010; Rosen & Kluemper, 2008).

Nowadays, SNSs have become the main platform for getting aassessment of products/services. 77% of the online Purchasing decision is based on users reviews on SNSs (Petersen, 2013). More than a million people go through the product/service review from SNS every week (Baldacci, 2015). According to Kim et al. (2015), weak ties collection is certainly associated with sharing information in SNSs. It was also concluded in their study that feeling of enjoyment was proved as influ-ential predictors of sharing activity in SNSs. Various benefits come through SNSs nowadays. E-commerce is often done through SNS like Facebook. Perceived ease of use, perceived usefulness, and subjective norms has a direct relationship with users on line buying decision-making (Sin et al., 2012). Jairak et al. (2010) ascertained that the most influencing elements that have consequences on users ITU social net-working websites are collaborative learning, pleasure, and familiarity. Information sharing has come to be very handy and famous for SNSs, and SNSs have the principal traits of spreading records via social inter-actions (Savolainen, 1999; Body and Ellison, 2007; Ferguson, 2008; Chen et al., 2012; Shu and Chuang, 2011; Aral and Walker, 2011; Chen et al., 2014; Wang and Vaughan, 2014). SNSs additionally play a vital role in economic development, and many corporations invest billions of euros in advertisement in SNSs (Cha et al., 2009; Bernoff and Li, 2008; Adar and Adamic, 2005 and Gruhl et al., 2004) confirmed that the records proclaimed model had been changed by way of the oral communication effect. Considerable research on the influences of SNSs on firms overall performance (Scullin et al., 2004; Yang et al., 2012; Luo and Zhang, 2013) and consumers conduct (Rishika et al., 2013; Goh et al., 2013). 

Mouakket, (2015) confirmed in his research that per-ceived usefulness, satisfaction, habit, enjoyment, and subjective norms are the widespread elements impac-ting users ITUSNSs. This paper focuses on how the social satisfaction factor influences intention. No research is available now on this context.

Literature Review

Sociability Motivation, Fashion Status, and ITUSNSs

Jairak et al. (2010) concluded that the significantly influencing factors those impact users ITUSNSs are learning collaboration, pleasure & familiarity. Shao et al. (2020) stated that the high experienced users are more interactive, and the low experienced users are negative in SNS. Highly motivated users spent more time on Facebook than those lowly motivated is found from Ross et al. (2009). From an open-ended response, it was exposed that nine motives were influential for usage of Facebook as social networking, and those motives are communication, uploading images/photos, entertainment, planning events, exchanging messages, going through posts of others, knowing people better, finding contact information and self-presentation (Pempek et al., 2009). Some researchers studied ex-planations and conduct based on weblog writing. Huang et al. (2007) recognized 5 motivating elements those influence running a blog nature (i.e., self-expression, existence documentation, comment, neighborhood discussion board engagement, and information searching). Nardi et al. (2004) observed 5 causes through realistic interviews, and these factors are documentation of individual life experiences, opinion/commentary, showing emotions, expressing an idea through written documents, and maintaining community forums. Similarly, Jung et al. (2007) found 5 factors for having a private blog comparable to Papacharissis, (2002) factors for having a private site: amusement, self-expression, knowledge sharing, time passing, and verbal exchange with ones family and close circle. On the other hand Hsu & Lin, (2008) found from their research that ease of use, enjoyment, and sharing of knowledge were the reasons for blogging in Taiwan. Some researchers studied to identify the motives through readerspoints of view. About half of the survey respondents go through blogs for enjoyment and to know their choices. By using the theoretical framework of usage and gratifications on pagers, it was discovered that being fashionable depended on additional motivation over studies (Leung and Wei, 1998). For the above reasons, users of SNSs think that belonging to a specific community of SNSs is their status issues and social identity (Currás et al., 2013). SNSs open a new field for people to share photos, manage their expected self-image, and be updated with recent trends. SNSs help establishes a connection with others (Gruen et al., 2006) and creates attitude. Information exchange in SNSs also changes users views (Soderlund and Rosegren, 2007). For this reason, Lee et al. (2008) found that attitudes of the users depended on other negative comments on SNSs. Another research by Hsu and Lu, (2004) identified that attitudes to using online games were also affected by social factors. 

From the above research background and discussion, it is proposed that-

H1: Sociability Motivation significantly impacts users ITUSNSs.  

H2: Fashion Status significantly impacts users ITU-SNSs.  

Perceived Entertainment and ITUSNSs

Little relation is positively connected to sharing information in SNSs (Kim et al., 2015). Their study similarly acknowledged that enjoyment was a noteworthy factor in sharing information in SNSs. We know many more benefits are gained from SNSs, such as digital marketing, e-commerce, online business, etc. Another research showed that the impact of SNSs on gratification with family time and family contentment differ for various reasons. Using SNSs supported families in building family time entertainable, connecting with members of family, and raising a feeling of belongingness.Unlikely, the uses of SNSs take family time, decrease attention during in-person meetings, and negatively compare (Sharaievska & Stodolska, 2017). Moon and Kim, (2001) described enjoyment as the delight the man or woman senses objective when engaging in a specific conduct or doing work and identified from their study that enjoyment/enter-tainment is a primary aspect of Internet acceptance. Davis et al. (1992) studied intrinsic inspiration in the discussion about Technology Acceptance Model (TAM). They concluded that intrinsic enjoyment greatly affects users intention for using computer technology. Van der Heijden, (2004) stated that per-ceived enjoyment is a vital issue influencing users ITU a method of amusement orientation. Affective exchange, information seeking, amusement, to get bandwagon are the four motives are influential for blogs users (Huang et al., 2008). From the above research background and discussion, it is proposed that 

H3:  Perceived Entertainment significantly impacts users ITUSNSs.  

Perceived Benefit and ITUSNSs

According to Godes & Mayzlin, (2004) and Ferguson, (2008) a social community is a package that permits a user to correlate, establish communication, content sharing, and community creation. Hawkins et al. (2007) mentioned that SNS is the system that allows people to exchange information. On the other hand, (Boyd and Ellison, 2008; Zhang and Jastram, 2006; Jiang, 2014) described SNSs are the media that permits customers to post a profile with the system where they have different customers with whom they exchange information and observe what other do thus they create a common interest community or group.It was seen that a constructive association between the perceived usefulness of buying from e-commerce available in SNSs and the intention to purchase through those sites. 

If the usefulness of online purchasing increases, the intention to purchase from SNSs or other online media also increases. The study also showed a significant association between ease of use of SNSs and intention to purchase from SNSs. The authors concluded that if the purchasing process, delivery, and payments using online media like SNSs become easier, then the ITU- SNSs media for e-commerce increases (sin et al., 2012). A study explored that the financial performance of SMEs gets a substantialconstructive impact from Facebook usage. It was likewise uncovered that the nonfinancial performance of SMEs has a constructive effect on Facebook in the arena of minimization of cos, on marketing and client service, enhanced customer relations, and better information nearness.Moreover, it was discovered that Facebook usage among SMEs has significant factors like compatibility, cost-effectiveness, and interactivity (Ainin et al., 2015; Davis, 1989) described usefulness as the users perception that using specific tools are supportive of improving users action of the work and then user senses it as positive. Many researchers concluded that a direct association remains between the usefulness of that system and the adaption of that technology/system (Yen et al., 2010; Pontiggia & Virili, 2010; Sledgianowski & Kulviwat, 2009; Zhou & Wang, 2009; Lee, 2009; Wu et al., 2007). It was exposed by the research that users feel good when the SNSs allow them to efficiently make and continue relation among the systems/ process, which enable new users to become adopt the system (Li & Bernoff, 2008; Pfeil et al., 2009). It was proved by some scholars that SNSs have a profoundimpact that results to the ITU- SNSs. From the above research background and discussion, the following hypothesis can be drawn –

H4: Perceived Benefits significantly impact users ITUSNSs

Social Networking Satisfaction and ITUSNSs

Oliver, (1980) defined user satisfaction as ones expected result with the outcomes. Anderson and Srinivasan, (2003) said that users state of happiness in his/her past online activities is users social networking satisfaction. Hunt, (1977) stated that the frame of mind is emotion, and satisfaction is the assessment of the frame of mind. Similarly Oliver, (1980, 1981) projected that in the case of consumption, gratification was the assessment of attitudes. Users are contented with SNSs with quality information, social presence, and economic value, and ultimately satisfaction with SNSs creates ITUSNSs (Chow et al., 2015). On SNSs, people get the community to support any time and this support satisfies users in this medium; as a result, users get eager to use SNSs (Oh et al., 2014).Now we can propose the following hypothesis:

H5: Social Networking Satisfaction significantly impacts users ITUSNSs.  

Sociability Motivation, Fashion Status, Perceived Entertainment, Perceived Benefit, and Social Networking Satisfaction

According to Currás et al. (2013) attitude isone of the influential factors which impact users satisfaction and loyalty to using SNSs. There are also many factors those impact users ITUSNSs such as sociability, entertainment gratifications, and perceived risks (psycho-logical, time loss, and social). SNSs influence infor-mation sharing, relationship quality, and social life satisfaction. It was discovered likewise that quality of personal attachment is impacted by information disseminating, and finally, it is significantly connected to satisfaction of public life. Finally, it was concluded that the connection between SNSs engagement and relationship quality is completely inclined by sharing of information. Nevertheless, the association between SNSs involvement and community life gratification is negatively affected (Dang, 2021). Now we can propose the following hypothesis:

H6:  Sociability motivation significantly affects Social Networking Satisfaction.

H7: Fashion/ Status partially affect Social Networking Satisfaction.

H8: Perceived Entertainment significantly affects Social Networking Satisfaction.

H9 Perceived Benefit significantly affects Social Net-working Satisfaction.

The Mediating role of Social Networking Satisfaction 

Many researchers stated a constructive association bet-ween life satisfaction and SNSs utilization intentions, with the rate of SNSs utilization and excessive SNSs utilization (Satici & Uysal, 2015; Rae & Lonborg, 2015; Oliveira & Huertas, 2015). Oliver, (1980) de-fined user satisfaction as ones justification of the disparity between past desire and outcome. In digital world, satisfaction is described as the users gratification concerning ones prior online user experience" (Anderson and Srinivasan, 2003, p. 125). Hunt, (1977) stated that the frame of mind is emotion, and satisfaction is the assessment of the frame of mind. Another research displayed that the influence of SNSs on satisfaction with household amusement and household satisfaction differ for various reasons. It was once found that using SNSs supported families in constructing amusing family vacations, connecting with household members, and raising feelings of belongingness. Oppositely, SNSs use takes family time, decreases interest during in-person meetings, and negatively compares (Sharaievska & Stodolska, 2017).

Now we can propose the following hypothesis

H10:  Social Networking Satisfaction partially medi-ates the influence of Sociability Motivation on users ITUSNSs. 

H11: Social Networking Satisfaction partially meditates the influence of fashion/status on users ITU- SNSs.

H12: Social Networking Satisfaction partially meditates the influence of Perceived Benefit on users ITU- SNSs. 

H13: Social Networking Satisfaction partially mediates the influence of Perceived Entertainment on users ITUSNSs.

METHODOLOGY

Measure

These questionnaires we used had been taken earlier research related to our topic and modified these questionnaires based on our purpose. We designed our questionnaire as renowned five-point Liker Scale. We measured sociability motivation, Fashion/status, and Perceived entertainment with four variables from Curras et al. (2013). The perceived benefit was calculated by three particulars taken from Main et al. (2019) and modified according to our topic. Social networking satisfaction by four variables was adopted from (Flavian et al., 2006; Janda et al., 2002; Oliver, 1980).   

Fig. 1: Conceptual model.
Sampling and data collection
To evaluate our proposed hypothesis, we gathered numerical statistical data. Then those data were used for further analysis. For this stage, we used structured questionnaires for gathering required data. The questionnaires were brought from the previous research; we used structured questionnaires. For the purpose of data collection, we used online and person-to-person direct interviews from Dhaka city. We collected 337 data and from which 26 were proved invalid, so the valid data was 311. Our respondents were from Bangladesh (on-line respondents), Dhaka (direct interview) and respondents ages ranged from 16-more to 55. We collected data from June to July 2022.  

Data Analysis
We used a two-step procedure to evaluate our data if the gathered data were validated or not (Anderson & Gerbing, 1988). This tactic is applied to findif the observed variable represents the latent constructs with a covariance matrix. We used smart PLS 3.3.3 for analyzing the measurement model along with structural model. We first calculated the factor loading, Cron-bach Alpha, Composite reliability, and Average variance extracted (AVE) to analyze the measurement model. After that, the structural model was analyzed by 311 data samples with smart PLS 3.3.3. 

RESULTS AND DISCUSSION:

From Table 1, it is proved that the collected data had a nice combination of males and females. Among the respondents, 55.31% were male and 44.69% female. Respondents were 31.19% of students. Furthermore, sub sequentially 13.18% was govt. Of job holders, 21.54% were private job holders, and 34.08% were unemployed, and they were the majority portion of the respondent. 

Table 1: Respondents (n=311) Demographic information

Variable

n

Percentage (%)

Gender

Male (M)

172

55.31

Female (F)

139

44.69

Age (years)

16-25

109

35.05

26-35

92

35.05

36-45

61

19.61

46-55

29

9.32

55 and above

20

6.43

Profession

Student

97

31.19

Govt job

41

13.18

Private job

67

21.54

Unemployed

106

34.08

Income

Less than 20000

203

67.22

20000-30000

41

13.18

30000-40000

37

11.90

40000-50000

21

6.75

More than 50000

9

2.893890675

Table 2 shows that about 84% of respondents liked Facebook as a SNS, and 83% got active on SNSsover three years. Half of the users spent their time twice a day on SNSs (53%), and from them, 31% spent more than three hours per day. 

Measurement model
We tested our projected model with a measurement model. This model justifies the validation of the pro-jected model. Convergent validity, discriminant vali-dity, and internal consistency were tested by this model. The proposed constructs internal consistency was justified based on the value of Cronbach Alpha and composite reliability (Hasan et al., 2021).
 
Table 2: Characteristics of SNSs users.

Characteristics

Favorite SNS

FB

261

83.92

Twitter

28

9.00

Instagram

12

3.86

Myspace

7

2.25

Other

3

0.96

Engagement

0.00

1

285

85.33

2

37

11.08

More than 2

12

3.59

Engagement history

 

Less than a year

17

5.47

One-Two years

16

5.14

Two-Three years

29

9.32

more than three years

249

80.06

Activity in a day

 

more than two times a day

178

57.23

One time in a week

62

19.94

One time a month

21

6.75

not sure

50

16.08

Active duration (a day)

 

Lesser than an hour

92

29.58

One-two hours

73

23.47

Two-three hours

47

15.11

more than three hours

99

31.83

From Table 3, we can see that Cronbach Alpha values range from 0.784-0.845 and composite reliability values are between 0.841-0.941. Both the values are greater than the accepted value thresholds (Bagozzi and Yi, 1988). Table 3 also represents that the average variance extracted (AVE) values are higher than 0.5. AVE was calculated to assess the convergent validity (Hasan et al., 2021). In addition, Table 4 proves that AVE values are higher than the squared correlation between the related construct and remainingitems with discriminant validity. For the structured equation model (SEM) proposed by Fornell & Larcker, (1981), the convergent and discriminant validity was verified earlier.  
Table 3: Findings from Measurement model.

Variables

Items

Factor Loading

Cronbachs Alpha (α)

Composite Reli-ability (CR)

Average Variance Extracted (AVE)

Sociability Motivations

0.845

0.923

0.806

To get update from my belongings, I like to use my favorite SNSs

0.926

To get the updated information I like to use my favorite SNSs

0.931

To improve my relationship with my belongings, I like to use my favorite SNSs

0.874

To feel others that I am thinking about

them, I like to use my favorite SNSs

0.819

Fashion/status

0.845

0.941

0.802

To appear as stylish, I like to use my

favorite SNSs

0.884

To uphold my status, I like to use my

favorite SNSs

0.905

To look fashionable, I Like to use my

favorite SNSs

0.896

To be up-to-date, I like to use my favorite SNSs

0.887

Perceived Entertainment

0.883

0.915

0.827

To get rid of boredom, I like to use my favorite SNSs

0.844

To make fun, I like to use my favorite SNSs

0.894

To pass my time, I like to use my favorite SNSs

0.922

To have amusement, I like to use my favorite SNSs

0.901

Perceived Benefit

0.791

0.842

0.695

SNSs are helpful in my life

0.821

SNSs will improve my life

0.845

SNSs will enhance my lifestyle.

0.874

SNS

0.793

0.841

0.724

I am satisfied what SNSs I use now.

0.789

I will continue using SNSs.

0.925

I did a good job getting involved in SNSs.

0.814

I am satisfied that I am getting services

from SNSs.

0.799

ITUSNSs

0.784

0.886

0.708

I have ITUSNSs

0.805

I have ITU the SNSs from the next year

0.814

Structural model
We tested our proposed hypothesis using the structured equation model (SEM) (Fornell & Larcker, 1981). Table 5 represents coefficient, t-statistics, p-value, and decisions. From Table 5, it is shown that the connotative sociability motivation and ITUSNSs was identified as significant (ß=0.181, t=3.383, p=.001) and accepted H1. Fashion/status has an insignificant relationship with the ITUSNSs (H2) (ß=0.108, t= 1.813, p=.07). So, thesevalues do not support the proposed hypothesis, so the decision was to reject this hypothesis. Perceived entertainment has a remarkable influence on the ITUSNSs (H3) (ß=0.137, t=2.817, p=.001). These values supported the H3. The perceived benefit was seen as notably associated with the ITU SNSs (H4) ((ß=0.239, t=4.382, p=.001). As a result, these values support H4. Moreover, this hypothesis was accepted. The influence of social networking satisfaction on ITUSNSs (H5) is very noteworthy as the values of ß=0.309, t=5.808, p=0) thus support H5. Social networking satisfaction has a constructive influence on sociability motivation (H6) ((ß=0.282, t=4.02, p=0), and the hypothesis (H6) was accepted. Fashion/ status has a strong affiliation with social networking satisfaction (H7) ((ß=0.316, t=5.352, p=0), which certainly supports H7. 

Table 4: Outcomes of discriminant validity.

SM

F/S

PE

PB

SNS

ITUSNS

SM

0.8875

F/S

0.202

0.893

PE

0.258

0.382

0.89025

PB

0.171

0.477

0.275

0.846666667

SNS

0.358

0.487

0.342

0.363

0.83175

ITUSNS

0.412

0.511

0.405

0.485

0.572

0.8095

Notes: SM=Sociability Motivation, F/S=Fashion/Status, PE=Perceived Entertainment, PB= Perceived Benefit, SNS=Social Networking Satisfaction, ITU SNS=Intention To Use Social Networking Sites.

Table 5: Path-coefficient and testing of Hypothesis.

Hypothesis

Relationships

Beta

T-statistics

P-Values

Decisions

H1

Sociability Motivation> ITUSNSs

0.181

3.383

0.001

Accepted

H2

Fashion/Status> ITU SNSs

0.108

1.813

0.07

Rejected

H3

Perceived Entertainment> ITUSNSs

0.137

2.817

0.001

Accepted

H4

Perceived Benefit> ITUSNSs

0.239

4.382

0.001

Accepted

H5

Social Networking Satisfaction> ITUSNSs

0.309

5.808

0

Accepted

H6

Sociability Motivation>Social Networking Satisfaction

0.282

4.802

0

Accepted

H7

Fashion/Status>Social Networking Satisfaction

0.316

5.352

0

Accepted

H8

Perceived Entertainment>Social Networking Satisfaction

0.118

1.889

0.047

Accepted

H9

Perceived Benefit>Social Networking Satisfaction

0.148

2.597

0.007

Accepted

H10

Sociability Motivation>Social Networking Satisfaction>

ITUSNSs

0.089

3.526

0

Accepted

H11

Fashion/Status>Social Networking Satisfaction> ITUSNSs

0.097

3.958

0

Accepted

H12

Perceived Entertainment>Social Networking Satisfaction> ITUSNSs

0.041

1.717

0.088

Rejected

H13

Perceived Benefits>Social Networking Satisfaction> ITU- SNSs

0.039

2.347

0.018

Accepted

Perceived entertainment and social networking satisfaction have remarkable association, and the values (ß=0.118, t=1.889, p=.047) support H8. Values represent (ß=0.148, t=2.597, p=.007), perceived benefit strongly correlates with social networking satisfaction, thus supporting H9. From Table 5, we can see that except fashionstatus, all the variables sociability motivation, perceived entertainment, perceived benefit, and social networking satisfaction notably influenced ITU SNSs. But, sociability motivation, fashion/ status, perceived entertainment, and perceived benefit had a noteworthy effect on social networking satisfaction. According to Table 5, we also see from the findings of mediating role of social networking satisfaction. Sociability motivation with social networking satisfaction affected ITUSNSs (H10) (ß=0.089, t=3.526, p=0). These results proved partial mediation. A strong association between fashion/status with social networking satisfaction and ITU SNSs is seen (H11) (ß=0.097, t=3.958, p=0), which showed partial medi-ation. Whereas perceived entertainment with social networking satisfaction has an insignificant impact on ITUSNSs (H12) (ß=0.041, t=1.717, p=0.88), and these values proved that complete mediation occurred in this case. Last, an insignificant impact was found on perceived benefits, including social networking satisfaction and ITUSNSs (H13) (ß=0.039, t=2.347, p=0.018). Thus, it means a partial mediation.

CONCLUSION AND RECOMMENDATIONS

This research revealed a strong connotation amid sociability motivation and ITUSNSs. This research result supports the earlier study by Currás et al., 2013. Practitioners may get help from this result as they understand what factors force users to use SNSs. Fashion/status has an insignificant relationship with ITUSNSs. This finding is the opposite of (Currás et al., 2013). This specifies that fashion/status is dis-similar from one country to another and one region to another regarding ITUSNSs. Reactionaries may get an idea not to promote SNSs focusing on fashionstatus issues regarding as same all over the world. This research showed that perceived entertainment has a notable effect on ITUSNSs. This result supports the findings (Currás et al., 2013). Perceived benefit and social networking satisfaction having a robust association with ITUSNSs. Moreover, we took a mediating variable to show how the mediating variable impacts the existing model. We took social networking satisfaction as a mediating variable. From our ana-lytical section, we can see that, social networking satis-faction partially mediates sociability motivation, fas-hion/status, and perceived benefit on ITUSNSs. It also completely mediates perceived entertainment on IT-USNSs. This mediatingrole indicates that not only sociability motivation, fashion/status, perceived entertainment, and perceived benefit impact on ITUS-NSs, but also social networking satisfaction has a great impact on users ITUSNSs. Practitioners should consider social networking satisfaction as a vitalaspect for analyzing users ITUSNSs. Moreover, practitioners should consider the prominence on making users satisfied while using SNSs; otherwise, users get demotivated toward using SNSs. Though our research is significant for implications in the practical field, some limitations have to be addressed for future study scope. 

Firstly, we collected our raw data in a short time frame, which indicates a business of data. So, future researchers should collect data over a long-time period. 

Secondly, we collected data from Bangladesh; the collected data volume was 311, which is very poor. To get more accurate results, future researchers should collect much more data. Thirdly, we conducted our survey for collecting data from online and face-to-face interview methods from people older than 15. Future researchers should consider those below 16 aged people as their respondents. Fourthly, our research mainly focused on the mediating role of social net-working satisfaction on ITUSNSs. Researchers may take any variable as the mediating factor. 

ACKNOWLEDGMENT

We are grateful to Dr. Appel Mahmud, Associate Professor, Department of Accounting and Information Systems, Begum Rokeya University, Rangpur, Bangla-desh, for providing proper guidelines in this research.

CONFLICTS OF INTEREST

We declared that we dont have any conflicts of in-terest to publish the present work.

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Article Info:

Academic Editor

Dr. Doaa Wafik Nada, Associate Professor, School of Business and Economics, Badr University in Cairo (BUC), Cairo, Egypt.


Received

September 10, 2022

Accepted

October 11, 2022

Published

October 19, 2022

Article DOI: 10.34104/cjbis.022.01120124

Corresponding author

Mohammad Rakibul Islam Bhuiyan

Dept. of MIS, Begum Rokeya University, Rangpur, Bangladesh.

Cite this article

Alam SMA, Bhuiyan MRI, Tabassum S, and Islam MT. (2022). Factors affecting users intention to use social networking sites: a mediating role of social networking satisfaction, Can. J. Bus. Inf. Stud., 4(5), 112-124. https://doi.org/10.34104/cjbis.022.01120124

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