International Journal of Management Science and Business Administration
Volume 4, Issue 6, September 2018, Pages 7-16
Social Media Usage and Firm Performance: Reflections from the Nigerian Telecommunication Sector
1 Akpan Ekom Etim, 2 Ibekwe Uzonna, 3 Worgu Steve C., 4 Nwangwu Chibuike E.
1 University of Port Harcourt, Department of Management, Nigeria
2 3 University of Nigeria, Department of Management, Nigeria
4 University of Nigeria, Department of Accountancy, Nigeria
Abstract: This study examines the relationship between social media usage and firm performance in the Nigerian telecommunication sector. A sample size of 76 people was determined from a population of 95 employees comprising customer service personnel, supervisors, and managers of four telecommunication outlets operating in Rivers State, Nigeria. The Pearson Product Moment Correlation Coefficient statistical technique was used to analyze data collected with the aid of the Statistical Package for Social Sciences computer software version 22. The study revealed that social media usage has a significant positive correlation with performance measures of profitability and market share. It was recommended that management of these firms need to give adequate attention to their social media platforms and use them extensively in rendering customer service, and for advertisement and promotion of their services which will elevate their performance.
Keywords: Social media usage, Advertising and Promotion, Firm performance, Profitability, Market share
Firm performance has continuously attracted scholars and experts’ attention, especially scholars in the area of management and operations/production management. It is seen as a means through which the growth and profitability of the firm are achieved (Gavrea, Ilies & Stegerean, 2011). In today’s business organizations, performance cannot be overlooked because it is the benchmark on which organizations measure their level of competitiveness in comparison to their contemporaries (Olusanya, Awotungase & Ohadebere, 2012).
As submitted by Umoh and Sylva (2016), any organization that fails to achieve a high level of performance stands a risk of “being mere ephemerals if they do not step up their productivity performance as they operate in a dizzying and turbulent business environment characterized by stiff competition, fluctuating demand for products, and rising cost of acquisition of productive resources”. Similarly, Gavrea, Ilies and Stegerean (2011) claim that ceaseless improvement in performance is the overall objective of businesses because it is through improvement in performance that the organization can grow, achieve profitability and expand their business frontiers.
Social media is a key factor in the success of 21st century business organizations, as noted by Culnan, McHugh and Zubillaga (2010), social media has the prospect of enhancing the value of business organizations by supporting the formation of computer-based customer circles that can encourage product branding, greater sales, better customer experience, and lead to new products development. According to Lam, Yeung and Cheng (2016), organizations’ social media usage might speed up information dissemination and knowledge acquisition and distribution within and outside the organizations, it also enhances the relationship with customers, suppliers, and improves other external collaborations.
Several studies have been carried out on the relationship between social media usage and firm performance (e.g., Dhar & Chang, 2009; Culnan, McHugh & Zubillaga, 2010; Kumar, Aksoy, Donkers, Venkatesan, Wiesel, & Tillmanns, 2010; Parveen, Jaafar, & Ainin, 2015; Baumöl, Hollebeek & Jung, 2016). Precisely, Dhar and Chang (2009) studied how the use of blogs and other types of social media outlets affect sales in the music sector, with special focus on user-generated content and concluded that “the internet has enabled the era of user-generated content, potentially breaking the hegemony of traditional content generators as the primary sources of legitimate information”. With its increasing popularity and effects, social media outlets, such as Youtube, Instagram, and Facebook are changing social, political and business norms. Although the usage of social media initiatives for business has attracted much scholarly attention in recent times, its relationship and effects on firms’ performance have not been exhaustively examined, especially in the Nigerian telecommunication sector. Yet, it is not clearly understood how telecommunication firms in the country can enhance their performance from their social media usage. This identified gap informed the need to study the relationship between social media usage and performance of telecommunication firms in the country. Thus, this study examines the correlation between social media usage including the use of social media for branding, advertising, promotion and customer relations and performance measures of profitability and market share of telecommunication firms in the country.
The telecommunication sector is an important component of the Nigerian economy, as it provides jobs for numerous youths, both Nigerians and foreigners (Sylva & Akpan, 2016). Every other sector of the economy relies on the telecommunication sector for fulfilling their communication needs, including communication between the organization and its external stakeholders, creating products awareness, and connecting with customers.
Despite the strategic role of the telecommunication sector in economic development, it has continuously failed to achieve its full potential (Alamutu, Hotepo, Oyeobu & Nwatulegwu, 2012; Sylva & Akpan, 2016). Oyedijo (2012) observed that, though the telecommunication firms have introduced a lot of improvement through innovative services such as electronic transfer of airtime and data, and other internet-based services. Some of the firms are still found to have information dissemination, service and products awareness and poor service quality. Customers still complain about the number of drop calls, unsolicited messages, poor attitude of customer service personnel, network congestion and interruptions during calls (Alamutu, et al, 2012; Sylva & Akpan, 2016). These deficiencies have led to the fluctuating performance of the sector. Although usage of social media to connect with customers seems inevitable, scholars and practitioners have continued to question the viability of social media investments and its influence on firms performance in terms of leading to increasing the market share, profitability and growth (Hoffman & Fodor, 2010; Kumar & Mirchandani, 2012). This has led to indecision by managers in incorporating social media usage in their company’s marketing strategy.
Thus, it is imperative to examine if the proper adoption of social media in the communication process of the telecommunication firms can enhance their performance in the areas of market share, profitability, and growth. Therefore, this study examines the correlation between social media usage and the performance of telecommunication firms in Nigeria.
2. Literature Review and Hypotheses Development
2.1 Theoretical Background
Several theories have been used to explain the phenomena of social media initiatives, which include “Unified Theory of Acceptance and Use of Technology (UTAUT)” (Curtis, et al 2010), Media Richness Theories (Koo, et al, 2011), and Uncertainty Reduction Theory (Sang, 2014). Chief amongst these theories is the Uncertainty Reduction Theory, which was developed by Berger and Calabrese (1975), and further expanded by Berger (1986; 2006). Thus, this study draws inspiration from the Uncertainty Reduction Theory.
According to Sang (2014), uncertainty reduction theory sought to understand and describe “how communication is used to reduce the uncertainty people face in interpersonal interactions”. This theory believes that uncertainty is a disadvantageous state which inspires “cognitive stress among people in interpersonal relationships”. Individuals seek to lessen uncertainty and the only avenue to achieve this is through communication. The theory propounded that individuals engage in communication to reduce uncertainty through different strategies – interactive, active, and passive communication.
According to Sang (2014) in interactive communication “information seekers engage in direct interaction with their targets to obtain uncertainty-reducing information through such methods as interrogation and self-disclosure”. In active communication, there is no direct interaction between information seekers and their targets. Instead, information seekers acquire uncertainty-reducing information indirectly from third parties who are familiar with the targets. The uncertainty reduction theory has been used in several academic fields including marketing and management (Morrison & Vancouver, 2000; Homburg et al., 2012; Walker, et al., 2013; Sang, 2014). Walker, et al (2013) used the uncertainty reduction theory to examine the likelihood of communication during the job recruitment process to lessen the fear of uncertainty by interviewees. Homburg, et al (2012) investigated the effect of communication on firm downsizing and customer uncertainty. Similarly, Sang (2014) studied the influence of social media initiatives on operational and financial performance relying on the uncertainty reduction theory. He posited that, when customers are given proper information, it reduces their level of uncertainty which promotes the firms’ performance.
2.2 Social Media and its Usage
Much attention has been given to the social media phenomenon in recent times by researchers. Articles on social media have appeared in several international journals including Marketing Science (e.g. Fader & Winer, 2012), Information Systems Research (e.g. Aral, Dellarcas & Godes, 2013), Journal of Management Information Systems (e.g. Luo & Zhang, 2013), Telematics and Informatics (e.g. Parveen, Jaafar, & Ainin, 2015) amongst others.
Social media is a platform that facilitates information sharing and participation from users of the media in order to create and/or distribute the content (Steenkamp & Hyde-Clarke, 2014). Likewise, Kaplan and Haenkein (2010) define social media as “a group of Internet-based applications that build on the ideological and technological foundations of Web 2.0, and that allow the creation and exchange of User Generated Content”. They separated social media into different categories such as social networking sites (e.g. Facebook, Google+), microblogs (e.g. Twitter, Instagram), collaborative project (including Wikipedia), content communities (such as, YouTube), virtual games worlds (including World of Warcraft), virtual social worlds (e.g. Second Life).
Likewise, Culnan, McHugh and Zubillaga (2010) propose that social media provides organizations with several business opportunities by helping them to build internet based customers communities through sales is enhanced, customer service satisfaction is guaranteed, and innovative ways of developing a new product are generated, all these add up to develop and sustain the brand. To leverage the numerous opportunities inherent in the usage of social media, telecommunication firms are now vigorously adopting social media platforms (such as Twitter, Facebook, Myspace) in relating with actual and potential customers (Ling, 2013). Currently, almost all the telecommunication firms in the country have a Facebook page. For example, MTN Nigeria has over 4 million followers/likes, while GLO has over 1.3 million likes to its Facebook page.
According to Parveen, Jaafar and Ainin (2015) there are several social media usages. These include “Information sharing and search, branding, advertising, conducting market research, reaching new customers, getting referrals, developing customers relations, communicating with customers, customer service activities and receiving customers feedback”. However, two of these initiatives which ranked highest on the reason of using social media was adopted as social media initiatives for this study. These are; the usage of social media for advertising and promotion, and for customer service activities.
2.3 The Concept of Firm Performance
The conceptualization, meaning, and importance of firm performance have been a recurrent topic in management scholars and experts gathering. Starting from the classical era, management was concerned on how to improve performance as can be seen in the first classical management theory – scientific management theory by Taylor (1911). Understanding the concept of performance and enhancing it has always been the concern of management practitioners, consultants, scholars, and theorists (Venkatrman & Ramanujam, 1986; Liao & Wu, 2009).
As noted by Liao and Wu (2009), despite the fact that the concept of performance is one of the most researched concepts in management and social science literature, its conceptualization, definition, has remained one of the most disputed. Though the importance of performance to firms cannot be disputed, it remains one of the controversial topics in management, with writings on this concept increasing on a daily basis, there seems to be no end in sight for argument on this all-important concept.
Firm performance has been classified into two kinds. Financial performance, which has to do with issues such as profitability, return on investment, asset growth (Venkatrman & Ramanujam, 1986), and non-financial performance, which is a concern with measures such as customer satisfaction, employee satisfaction, shareholder wealth maximization, and customer loyalty (Venkatrman & Ramanujam, 1986). However, in this study, profitability and market share were adopted as measures of firm performance as proposed by Hamann, Schiemann, Bellora, and Guenther (2013) and used by several other scholars (e.g. Umoh & Sylva, 2016).
2.4 Social Media Usage and Firm Performance
There has been an increase in the debate concerning the importance and benefits of social media initiatives by scholars and practitioners (Lutz, 2012). The controversy surrounding the usage of social media has led to the investigation of its impact on a number of organizational outcomes and to find out if the investment on social media equates the benefits derived. Hoffman and Fodor (2010), and Kumar and Mirchandani (2012) noted that despite the seeming importance of social media on customer relations, firms are skeptical about its usage and are “questioning the return on investment (ROI) of social media investments and often hesitate to integrate social media initiatives in their marketing strategy”.
Others believe that social media which is symbolized by user-generated content, is more efficacious in customer relations when compared to the traditional communication channel and it positively influences users’ attitudes and behaviors (Thackeray, Neiger, Hanson & Mckenzie, 2008). Due to the perceived importance of social media in the achievement of organizational goals, telecommunications as well as firms in other sectors have started to integrate the use of social media into their marketing strategies (Gobry, 2011), some have gone ahead to develop their own internal social media platforms (Murphy, 2010). A study by Harvard Business School as far back as 2010 revealed that 79% of businesses in the United States had adopted social media as part of their communication strategies, while 21% were preparing to launch their social media initiatives.
Figure 1: Conceptual Model
Source: Conceptualised by the authors, 2018
Based on the literature review and conceptual framework above, it was hypothesized that there is no significant relationship between social media usage (advertising and promotion, and Customer Services) and firm performance (profitability and market share). Specifically, the following hypotheses are formulated:
Hypothesis 1: There is no significant relationship between the use of social media for advertising and promotion, and profitability of the telecommunication firms.
Hypothesis 2: There is no significant relationship between the use of social media for advertising and promotion, and market share of the telecommunication firms.
Hypothesis 3: There is no significant relationship between the use of social media for customer services and the profitability of the telecommunication firms.
Hypothesis 4: There is no significant relationship between the use of social media for customer services and market share of the telecommunication firms.
3. Research Methodology
In this study, the cross-sectional survey research design was adopted in carrying out the study. This was suitable since the data had to be collected from the study population at a single point in time to conduct the research (Gravetter & Walnau, 2000; Gravetter & Forzano, 2009).
The population of this study comprises employees of telecommunication firms in Nigeria. However, the study concentrated on the mobile phone (GSM) operators only. Data from the regulatory body for the sector – Nigeria Communication Commission (www.ncc.gov.ng) shows that there are 5 GSM operators in the country, out of which 4 have functional offices in Rivers State. However, for the purpose of this study, the management staff, supervisors and customer service attendants of the branches of these firms that were first established in the state were chosen. Therefore, the accessible population consisted of 95 employees. The Krejcie and Morgan (1970) table was used to determine a sample size of 76. A structured questionnaire was sent to the respondents, out of which 62 copies were returned, representing 82% returned rate. However, nine copies were not used for the final analyses due to inconsistent and incomplete information. Therefore, 53 copies of the questionnaire were used for the final analyses.
3.1 Operational Measures of Variables
All the statement items were scaled on a five-point Likert scale. The scales were anchored at both ends in the way that 5 = strongly agree and 1 = strongly disagree. Social media usage was dimensionalized using advertising and promotion, and customer services. It was measured using 8 statement items such as “in our firm, we continuously advertise our products/services on the social media”. Similarly, profitability and market share were adopted as measures of firm performance. A 6-item instrument was used to describe the construct which was adapted from Hamann, et al. (2013), and subsequently modified by Umoh and Sylva (2016) to suit the Nigerian working environment. It contained items such as “Our company’s return on sales this year has improved compared with last year; we have added more customers to our customer base this year”.
4. Data Analysis and Discussions
4.1 Validity and Reliability of Instrument
Research instrument validity is “the extent to which an instrument measures what it is supposed to measure” (Kimberlin & Winterstein, 2008). In other words, an instrument is said to be valid, when it is confirmed to measure what it intends to measure. The validity of the instrument used for this study was confirmed through face and content, convergent and discriminant validity. The face validity of the instrument was confirmed through the administration of the instrument to experts in the field and academics for their scholarly inputs. The instrument was also first administered on a pilot basis to the same managers of the selected telecommunication firms for their constructive criticisms and opinion, they were however satisfied with the instrument. Also, the researcher took the time to study numerous research works of contemporary scholars in the concerned area to ensure the content validity of the instrument (Nunnaly & Bernstein, 1994).
On the other hand, the Reliability of a research instrument, which is also known as internal consistency, is the ability of the instrument to produce similar results over a period of time and in separate studies. Joppe (2000) defines reliability as “the extent to which results are consistent over time”, while Golafshani (2003) submitted that, if a study can return a similar result when carried out using a similar methodology, such research can be considered to be reliable. The reliability of the instrument for this study was confirmed via the Cronbach Alpha, Average variance extracted (AVE) and Composite reliability. The output of validity and reliability analyses which were carried via SPSS version 22 are shown in tables 1 and 2.
To verify the convergent validity, factor loadings of individual items were observed. Each item loadings are above 0.6, while the averages of the item-to-factor loadings in the model were above the 0.5 thresholds (Bagozzi & Yi, 1988; Hair, Black, Babin, Anderson & Tatham, 2006). These results show the convergent validity of the items.
Table 1: Internal consistency and convergent validity
|Convergent validity||Internal consistency reliability|
|Loadings||Indicator reliability||AVE||Composite reliability c||Reliability Coefficient||Cronbach’s alpha|
|>0.70||>0.50||>0.50||>0.70||>0.70||0.70 – 0.90|
|Note: ADP = Advertising and Promotion, CSA = Customer service activities, PR =Profitability, MKS = Market Share|
Table 2: Construct Validity and Reliability
|Cronbach Alpha||Composite Reliability||AVE||ADP||CSA||PR||MKS|
|Note: AVE = Average Variance Extracted, ADP = Advertising and Promotion, CSA = Customer Service Activities, PR = Profitability, MKS = Market Share. Diagonal elements are the square root of Average Variance Extracted (AVE) between the constructs and their measures. Off-diagonal elements are correlations between constructs.|
To ensure discriminant validity, the square roots were calculated for the AVEs. This shows the extent that a construct is different from others. As shown in the model, the correlation between the square root values with other variables values shows that the square root values for each AVE are greater than the inter-construct correlations. Thus, it indicates the acceptable discriminant validity of all constructs (Fornell & Larcker, 1981).
4.2 Hypotheses Testing
In order to confirm the relationship between social media usage and firm performance, the Pearson Product Moment Correlation Coefficient was used to analyze data generated from the responses from the study elements. The Pearson Product Moment Correlation Coefficient (r) was chosen since the study involves the testing of the relationship between two variables (Pallant, 2013; Hair, Hult, Ringle & Sarstedt, 2014). Also, data collected were transformed to suit this statistical tool.
The tables below show the results obtained from the analysis of data based on the hypotheses stated earlier in this work.
The first hypothesis states that there is no significant relationship between the use of social media for advertising and promotion and profitability. The table below shows the outcome of the analysis.
Table 3: Correlations between Advertising and Promotion, and Profitability
|Advertising and Promotion||Profitability|
|Advertising and Promotion||Pearson Correlation||1||.716*|
|*. Correlation is significant at the 0.05 level (2-tailed).|
The analysis reveals a strong positive correlation between the use of social media for advertising and promotion, and profitability of the telecommunication firms, with r = .716, pv < 0.05, and n = 53. Based on the conditions stipulated by Cohen (1988), the null hypothesis was rejected and the alternative accepted.
There is no significant relationship between using social media for advertising and promotion, and market share of the telecommunication firms.
Table 4: Correlations between Advertising and Promotion, and Market Share
|Advertising and Promotion||Market Share|
|Advertising and Promotion||Pearson Correlation||1||.741*|
|Market Share||Pearson Correlation||.741*||1|
|*. Correlation is significant at the 0.05 level (2-tailed).|
Table 4 above, indicates that there exists a strong positive correlation between the use of social media for advertising and promotion, and market share of the telecommunication firms, with r = .741, Pv < 0.00, n = 53. Thus, the null hypothesis was rejected and the alternative was accepted.
There is no significant relationship between using social media for rendering customer services and the profitability of the telecommunication firms.
Table 5: Correlations between Customer Services and profitability
|Customer Services||Pearson Correlation||1||.647*|
|*. Correlation is significant at the 0.05 level (2-tailed).|
Table 5 above, indicates a moderate positive correlation between the use of social media for advertising and promotion and profitability of the telecommunication firms, with r = .647, Pv < 0.05, n = 53. Thus, the null hypothesis was rejected and the alternative accepted.
There is no significant relationship between using social media for customer services and market share of the telecommunication firms.
Table 6: Correlations between Customer Services and market share
|Customer Services||Market Share|
|Customer Services||Pearson Correlation||1||.832*|
|Market Share||Pearson Correlation||.832*||1|
|*. Correlation is significant at the 0.05 level (2-tailed).|
Table 6 revealed a strong positive correlation between the use of social media for customer services and market share of the telecommunication firms, with r = .832, Pv < 0.05, n = 53. Thus, the null hypothesis was rejected and the alternative was accepted.
The study empirically examined the causal relationship between social media initiatives (the use of social media for advertising and promotion, and customer services). The analyses conducted revealed that social media initiatives positively and significantly correlated with the measures of telecommunication firms’ performance. This may have been the reason, why almost all the telecommunication firms are exploring opportunities presented by the flexible nature of social media in the image making, product branding, promoting, advertising and endearing their services to the clients. Example of this is the introduction of ‘ON THE GO’ by Airtel Nigeria, this platform allows subscribers to present their complaints any time of the day, using the WhatsApp.
This finding also corroborates the findings of several other studies by renowned scholars, who submitted that social media initiatives have a positive relationship with firm’s performance (e.g., Dhar & Chang, 2009; Culnan, McHugh & Zubillaga, 2010; Aral, Dellarocas & Godes,2013; Lam, Yeung & Cheng, 2016). Specifically, Lam, Yeung, and Cheng (2016) investigated the influence of social media initiatives on the firms’ operational efficiency and innovativeness and came to the conclusion that social media usage leads to be the development of new ideas and result in efficiency. Similarly, Aral, Dellarocas and Godes (2013) submit that social media usage promotes business transformation. In this manner, Sang (2014) examined “social media initiatives and operational and financial performance” while Parveen, Jaafar hand Aimin (2015) studied “social media usage and organizational performance”, both studies obtained similar results, that social media initiatives positively correlate with the performance of the firms. Likewise, Amue, Umoh and Ngaage (2012) opine that increasing market share in the long-run is dependent on the ability to retain customer loyalty which can be achieved through effective communication, which social media helps to achieve in this new dispensation.
5. Conclusion and Recommendations
Based on the analyses and the subsequent findings it, therefore, implies that management of these firms needs to give adequate attention to their social media platforms. It is thus recommended that:
- More attention should be given to social media by telecommunication companies when branding their products and services since it promotes performance.
- Advertising and promotions should be done more using social media such as Facebook, Twitter, Myplace so as to improve the feasibility of the firm and create a better image for them.
- Customer service activities should be carried out on social media. This will speed up the time taken to address customers’ complaints.
- Information about products and services should be made available to the customer in the firm’s social media platforms for easy accessibility.
- Alamutu, S. A., Hotepo, O. M., Oyeobu, A. J. & Nwatulegwu, B. I. (2012). An evaluation of total quality management practices on business performance of the Nigerian telecommunications sector: A case study of MTN Nigeria Limited. ICCEM, 155 166.
- Amue, G. J., Umoh, G. I. & Ngaage, K.T. (2012). Dynamic behavior in customers’ switching and market share analysis: The Markov model perspectives. Global Journal of Management and Business Research, 12(17), 1-8.
- Aral, S., Dellarocas, C., & Godes, D. (2013). Social media and business transformation: A framework for research. Information Systems Research. 24(1), 3-13. Crossref
- Bagozzi, R.P. & Yi, Y. (1988). On the evaluation of structural equations models. Journal of Academy of Marketing Science, 16(1), 74-94. Crossref
- Baumöl, U., Hollebeek, L. & Jung, R. (2016). Dynamics of customer interaction on social media platforms, Electron Markets.
- Berger, C. R. (1986). Uncertain outcome values in predicted relationships uncertainty reduction theory then and now. Human Communication Research, 13(1), 34-38. Crossref
- Berger, C. R., & Calabrese, R. J. (1975). Some explorations in initial interaction and beyond: Toward a developmental theory of interpersonal communication. Human Communication Research, 1(2), 99-112. Crossref
- Cohen, J. W. (1988). Statistical power analysis for behavioural sciences, (2nd). New Jersey: Hilladale, Lawrence Erlbaum Associates.
- Culnan, M. J., McHugh, P. J., & Zubillaga, J. I. (2010). How large U.S. companies can use Twitter and other social media to gain business value. MIS Quarterly Executive, 9(4), 243-259.
- Curtis, L., Edwards, C., Fraser, K.L., Gudelsky, S., Holmquist, J., Thornton, K., Sweetser, K. D. (2010). Adoption of social media for public relations by nonprofit organizations. Public Relations Review, 36 (1), 90–92. Crossref
- Dhar, V. & Chang, E. (2009). Does chatter matter? The impact of user-generated content on music sales. Journal of Interactive Marketing, 23 (4), 300-307. Crossref
- Fader, P. S., & Winer, R. S. (2012). Introduction to the special issue on the emergence and impact of user-generated content. Marketing Science, 31 (3), 369–371. Crossref
- Fornell, C. & Larcker, D.F. (1981). Evaluating structural equations models with unobservable variables and measurement error. Journal of Marketing Research, 8(1), 39-50, 1981. Crossref
- Gavrea, C., Ilies, L. & Stegerean, R. (2011) Determinants of organizational performance: The case of Romania. Management and Marketing Challenges for the Knowledge Society, 6(2), 285-300.
- Gobry, P. (2011). P&G opens Facebook stores, paving the way for Facebook’s next billion dollar business. Retrieved on 23/04/2017, from http://www.businessinsider.com/procter gamble-facebook-stores-2011-6.
- Golafshani, N. (2003). Understanding reliability and validity in qualitative research. The Qualitative Report, 8(4), 597-606.
- Gravetter, F. J., & Wallnau, L. B. (2000). Statistics for the behavioral sciences (5th edn).Belmont, CA: Wadsworth.
- Gravetter, F., & Forzano, L.-A. (2009). Research methods for the behavioral sciences (3rd). Belmont, CA: Wadsworth Cengage Learning.
- Hair, J.F., Black, W.C., Babin, B.J., Anderson, R.E. & Tatham, R.L. (2006). Multivariate data analysis. New Jersey: Prentice-Hall, Upper Saddle River.
- Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2014). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks, CA: SAGE.
- Hamann, P. M., Schiemann, F., Bellora, L. & Guenther, T.W. (2013). Exploring the dimensions of organizational performance: A construct validity study. Organizational Research Methods, 16(67), 67-87. Crossref
- Harvard Business Review Analytic Services (2010). The new conversation: Taking social media from talk to action. Boston, MA: Harvard Business Review.
- Hoffman, D. L. & Fodor, M. (2010). Can you measure the ROI of your social media marketing? MIT Sloan Management Review, 52(1), 41-49.
- Homburg, C., Klarmann, M., &Staritz, S. (2012). Customer uncertainty following downsizing: The effects of extent of downsizing and open communication. Journal of Marketing, 76(3), 112-130. Crossref
- Kaplan, A. M. & Haenlein, M. (2010). Users of the world, unite! The challenges and opportunities of social media. Business Horizon, 53 (1), 59–68. Crossref
- Kimberlin, C. L. & Winterstein, A. G. (2008). Validity and reliability of measurement instruments used in research. American Society of Health System Pharmacists, 65:2276 84. Crossref
- Koo, C., Wati, Y. & Jung, J. J. (2011). Examination of how social aspects moderate the relationship between task characteristics and usage of social communication technologies (SCTs) in organizations. International Journal of Information Management, 31 (5), 44 459. Crossref
- Krejcie, R. V. & Morgan, D.W. (1970). Determining sample size for research activities. Educational and Psychological Measurement, 30, 607-610. Crossref
- Kumar, V. & Mirchandani, R. (2012). Increasing the ROI of social media marketing. MIT Sloan Management Review, 54(1), 55-61.
- Kumar, V., Aksoy, L., Donkers, B., Venkatesan, R., Wiesel, T., & Tillmanns, S. (2010). Undervalued or overvalued customers: capturing Total customer engagement value. Journal of Service Research, 13(3), 297–310. Crossref
- Lam, H. K. S., Yeung, A. C. L., & Cheng, T .C. E. (2016). The impact of firms’ social media initiatives on operational efficiency and innovativeness. Journal of Operations Management, 47/48, 28–43. Crossref
- Liao, S. & Wu, C. (2009). The relationship among knowledge management, organizational learning, and organizational performance. International Journal of Business and Management, 4(4), 64-76. Crossref
- Ling, B. (2013). 18 million obvious secrets about Facebook business pages you need to know today. Social Times (July 26). http://www.insidefacebook.com/2017/04/25/18-million obvious-secrets-about-facebook-business-pages-you-need-to-know-today/.
- Luo, X. & Zhang, J. (2013). How do consumer buzz and traffic in social media marketing predict the value of the firm? Journal of Management Information Systems, 30(2), 213-238. Crossref
- Lutz, A. (2012). Facebook is not driving e-commerce as much as some retailers hoped. Retrieved on 23/04/2017, from http://www.washingtonpost.com/business.
- Morrison, E. W., & Vancouver, J. B. (2000). Within-person analysis of information seeking: The effects of perceived costs and benefits. Journal of Management, 26(1), 119-137. Crossref
- Murphy, G. D. (2010). Using web 2.0 tools to facilitate knowledge transfer in complex organisational environments: A primer. Paper presented at the ICOMS Asset Management Conference 2010, University of Adelaide, South Australia.
- Nunnally, J. C. & Bernstein, I. H. (1994). Psychometric theory (3rd). New York: McGraw Hill.
- Olusanya, S.O., Awotungase, S. A. & Ohadebere, E. C. (2012), Effective planning and organizational productivity (A case study of Sterling Bank Nigeria Plc).IOSR Journal of Humanities and Social Sciences, 5(5), 31-39. Crossref
- Oyedijo, A. (2012). Strategic agility and competitive performance in the Nigerian telecommunication industry: An empirical investigation. American International Journal of Contemporary Research, 2(3); 227-237.
- Parveen, F., Jaafar, N. I. & Ainin, S., (2015). Social media usage and organizational performance: Reflections of Malaysian social media managers. Telematics and informatics, 31 (3), 492-510. Crossref
- Sang, L. K. (2014). The impact of social media initiatives on operational and financial performance outcomes: Two empirical studies. An unpublished thesis submitted to The Hong Kong Polytechnic University.
- SteenKamp, M. & Hyde-Clarke, N. (2014). The use of Facebook for political commentary in South Africa. Telematics Inform, 31 (1), 91–97. Crossref
- Sylva, W. & Akpan, E. E. (2016). The impact of structure on strategy implementation among telecommunication firms in Nigeria. European Journal of Business and Management, 8(14), 59-68.
- Thackeray, R., Neiger, B. L., Hanson, C. L. & McKenzie, J. F. (2008). Enhancing promotional strategies within social marketing programs: use of Web 2.0 social media. Health Promot. Pract. 9(4), 338–343. Crossref
- Umoh, G. I. & Sylva, W. (2016). Capacity planning and corporate productivity performance in the Nigerian aviation industry. International Journal of Business and Public Administration, 13(1), 21-35.
- Venkatraman, N., & Ramanujam, V. (1986). Measurement of business performance in strategy research: A comparison of approaches. The Academy of Management Review, 11(4), 801 814. Crossref
- Walker, H. J., Bauer, T., Cole, M., Bernerth, J., Feild, H., & Short, J. (2013). Is this how I will be treated? Reducing uncertainty through recruitment interactions. Academy of Management Journal, 56(5), 1325-1347.