Int. J. Internet Marketing and Advertising, Vol. X, No. Y, xxxx
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Adoption of social networks marketing by SMEs: exploring the role of social influences and experience in technology acceptance Iryna Pentina*, Anthony C. Koh and Thuong T. Le Department of Marketing and International Business, University of Toledo, 2801 W. Bancroft St. Toledo, OH 43606-3390, USA Fax: 419-530-4610 E-mail:
[email protected] E-mail:
[email protected] E-mail:
[email protected] *Corresponding author Abstract: As social media increasingly penetrate the business world, it is important to understand the underlying reasons for companies to adopt social networks marketing (SNM). This study extends the technology acceptance model (TAM) to explore the role of social influences in the context of SNM technology adoption by small and medium companies, and considers how the temporal aspect of new technology adoption affects this relationship. Our findings show that adoption of SNM is strongly influenced by social influences from experts, competitors, and customers. These social influences affect intention to adopt this new technology both directly, and by affecting the perceptions of the technology usefulness. For SMEs already using SNM, social influence is the only strong determinant of the intention to continue employing this marketing technology, with the amount of experience with SNM strengthening this relationship. Keywords: social networks marketing; SNM; social media; technology acceptance model; TAM. Reference to this paper should be made as follows: Pentina, I., Koh, A.C. and Le, T.T, (xxxx) ‘Adoption of social networks marketing by SMEs: exploring the role of social influences and experience in technology acceptance’, Int. J. Internet Marketing and Advertising, Vol. X, No. Y, pp.000–000. Biographical notes: Iryna Pentina is an Assistant Professor at the University of Toledo. Her research interests include social and interactive marketing, applicability of marketing theory to online sales situations, internet retailing, and virtual communities. She has published papers in journals such as the European Journal of Marketing, Journal of Retailing, Journal of Electronic Commerce Research, European Journal of Innovation Management, Journal of Consumer Behaviour and Journal of Customer Behaviour. Anthony C. Koh is the Chair and an Associate Professor at the Department of Marketing and International Business, University of Toledo. His major research works have appeared in several publications, including International Marketing Review, Journal of Business Research, Journal of Global Marketing, Journal of the Academy of Marketing Science, Journal of Teaching in International Business, International Business Review and the Journal of Electronic Commerce Research. Copyright © 200x Inderscience Enterprises Ltd.
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I. Pentina et al. Thuong T. Le is a Professor of marketing, e-business and supply chain management at the College of Business Administration, University of Toledo. His teaching and research focus on B2B e-commerce, internet marketing, social computing, supply chain management and global business. His recent research has appeared in Industrial Marketing Management, Electronic Markets, Electronic Commerce Research and International Journal of Services Technology and Management.
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Introduction
Social media is the fastest-growing marketing channel in the world (Coremetrics, 2010). Expenditures on social media marketing in the USA are predicted to grow 34% annually and reach $3.1 billion in 2014 (Forrester Research, 2009). This trend reflects the paradigm shift within advertising and marketing communications industry: from one-way, ‘cluttered’ mass media to interactive, narrowly targeted approaches and towards synergistic integration of all company communications. As opposed to paid online advertising (banner, text, and search), social networks marketing (SNM) involves initiating viral consumer-to-consumer communications by creating company/brand fan pages and managing promotions and public relations within most popular social networks, such as Facebook, YouTube, and Twitter. Such social networks applications as product sharing and voting, collaborative design, and product launch announcements may provide relevance, immediacy, and convenience to customers, as well as publicity and brand name recognition to the company (Evans, 2009). This marketing medium appears to be especially advantageous for small and medium-size enterprises (SMEs) due to its moderate costs, and the flexibility with which smaller organisations can adapt social networks for both marketing and new product development. While the advantages of SNM are strongly supported by experts, the decision to adopt this new marketing technology by SMEs is not automatic: challenges include lack of demonstrable results, and difficulties in developing measurement metrics to estimate its effectiveness (Internet Advertising Bureau, 2010). These challenges, as well as the risk of potential negative viral spread damaging a company’s reputation, pose obstacles to extensive SNM adoption. In spite of this, increasing numbers of businesses and brands make social networks an integral part of their marketing strategy. Understanding the drivers of SNM acceptance by SMEs may help provide practical advice and guidance to companies in the process of strategic marketing planning and budget allocation, as well as assist academics in further development of strategic marketing theory in the area of SNM. The technology acceptance model (TAM) postulates that for an organisational decision-maker, a decision to adopt a new technology is mainly based on the perceptions of its ease of use and usefulness (Davis, 1989). Since using social networks does not require considerable technological skills, but instead relies on the synergistic employment of existing marketing, PR, and customer service skills, and because SNM usefulness in terms of measurable marketing performance is difficult to assess, other factors may be responsible for the decision to adopt SNM. This paper proposes the role of social influences (SIs) (by industry leaders, competitors, and customers) as an additional antecedent to SNM acceptance by small and medium companies, and compares its role at different adoption stages. In the remainder of the paper, we develop our theoretical
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model, describe data collection and testing methods, report and discuss the results, and provide conclusion, managerial recommendations, and suggestions for future research.
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SNM and small businesses
Recent developments in Web 2.0 and 3G/4G technologies have created a major paradigm shift in business-to-customer relationships: a shift in information control. Customers are no longer passive ‘receivers’ of company and brand-related marketing messages. Instead, they are engaged in initiating conversations with and providing feedback to businesses, as well as in creating and sharing content among themselves. Social network sites allow users to create and share personal profiles, establish and develop new connections, and provide and acquire information in an interactive manner (Boyd and Ellison, 2008). Open access to other members’ contacts provides consumers unprecedented opportunities to control the process of marketing communications by exponentially spreading viral messages about products, brands, and/or customer service that can be either detrimental or beneficial to any business. Given the remarkable size and growing marketing potential (e.g., Facebook with its 500 million members commands a 20% share of the US online advertising, social networks are acquiring strategic significance for companies that appreciate their capacity for targeting, promotion, public relations, and market research (Nielsen, 2010). According to eMarketer (2010), US online social network and word-of-mouth marketing spending will grow 35% in 2010 to over $1 billion, and will exceed $3 billion in 2012. This is substantially higher than paid social network advertising that will rise 7.1% in 2010 (eMarketer, 2010). Currently, most prevalent SNM practices involve creating and operating a company’s fan page, managing promotions, maintaining public relations, and conducting market research. Other activities include providing customer support, encouraging customer reviews and discussions, and recruiting (McCorvey, 2010). Both academics and practitioners agree that the key to business success with SNM is the ability to engage followers. For example, Organize.com, an online seller of house and office products, invited its followers to a two-hour Twitter party, bringing in 323 orders and $15,000 in incremental sales. The online clothes store WetSeal has increased sales by 10% and an average order value by another 10% by launching a community section of their site where fans can design their own ensembles and publish them to the community for reviews. Zappos (an online shoe store) uses Twitter to address customer service issues and to reinforce their reputation by encouraging employees to participate in Twitter. It has been noted that smaller companies are more suited to utilise SNM due to their greater flexibility and higher need to contain marketing communications costs (Harris and Rae, 2009). Indeed, 91% of the Inc. 500 companies used at least one social media tool in 2009 (up from 77% in 2008), and 43% of the 2009 Inc. 500 companies reported that social media was very important to their marketing strategy (Schweitzer, 2009). While certain successes with using SNM are widely publicised and analysed, and the advantages of using these media by small and medium businesses are extensively discussed, the decision to adopt SNM as a marketing tool by SMEs is not automatic (Drossos et al., 2011). As the 2009 GfK Roper survey of 500 businesses with fewer than 100 employees shows, 76% of executives find sites like Facebook, Twitter, and LinkedIn to be of little help in finding new sales leads. In addition, 86% of those surveyed do not use social networking sites for business advice or information (Schweitzer, 2009). It also
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found that most of these businesses had not used online networks at all because they considered it a waste of time (Economist, 2010). According to the Internet Advertising Bureau (2010), major challenges of SNM include lack of demonstrable return on investment (74% of respondents), as well as absence of reliable reporting metrics for this emerging marketing tool (64% of respondents). Similarly, a Marketing Sherpa study found inability to measure return on investment a major barrier to social media marketing for 43% of responding organisations (Marketing Sherpa, 2009). Metrics such as the number of viewers, visitors, friends, or followers do not automatically translate to higher conversions, order value, or sales. It is true that given their viral characteristics, SNM may be more effective in building brand awareness and enhancing brand reputation than generating leads and increasing sales (Barnes and Hair, 2009). But even in this function, SNM is only one part of integrated marketing communications, and it is difficult to ascertain its contribution compared to paid advertising and other types of promotion. Another issue is the length of time required for each new SNM tactic to work and the resulting problem of measurement timing. Finally, quantifying engagement (the main goal of SNM) that does not necessarily parallel numbers of friends, subscribers, tweets, and retweets is still an unresolved issue. In spite of the existing scepticism regarding SNM effectiveness and measurability, ever increasing number of companies worldwide plan to incorporate it into their marketing programmes and to shift resources away from traditional to SNM. The 2010 Customer Engagement Report by cScape/eConsultancy shows that 61% of more than 1,000 surveyed marketers worldwide plan to increase investment in social media in 2010 (Econsultancy, 2010). Forrester Research also predicts that social media will see the steepest growth of any channel, a 34% CAGR over the next five years, exceeding $3 billion by 2014 (Forrester Research, 2009). Given the aforementioned lack of demonstrable success and adequate measurement metrics, other factors (e.g., striving to be the first mover or the bandwagon effect) may be responsible for the adoption of the SNM technology by small and medium companies. This study applies the extended TAM to explore the role of SIs in the context of SNM technology adoption by small and medium companies, and considers how the temporal aspect of new technology adoption affects this relationship.
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Conceptual framework and hypotheses development
The TAM is a theory that predicts intentions to adopt a new technology by organisational users/decision-makers (Davis, 1989; Davis et al., 1989). It appears to be especially applicable to the SME context that is characterised by fewer hierarchical management levels, and as a result, a more direct decision making process (Thrassou and Vrontis, 2008). TAM has been widely applied and empirically supported to predict the adoption of information technology (Davis, 1989; Taylor and Todd, 1995), computers (Davis et al., 1989), spreadsheets (Mathieson, 1991), technology-based self-service (Dabholkar and Bagozzi, 2002), e-business (Parker and Castleman, 2009), mobile marketing (Sultan et al., 2009), mobile commerce (Wu and Wang, 2005), and many other information and business-related technologies. Rooted in the social-psychology theory of reasoned action (Fishbein and Ajzens, 1975) and theory of planned behaviour (Ajzen, 1991), TAM posits that a user’s (decision-maker’s) behavioural intention to use a technology is determined by two beliefs: perceived usefulness (PU) and perceived ease of use (PEU). PU is the extent to which a person believes that using the technology will enhance job
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performance, and PEU is the belief that using the technology will be free of effort. In addition, PEU is posited to positively affect PU (Venkatesh and Davis, 2000). When applied in varied technology and organisational contexts, PU has been very robust in predicting user acceptance (standardised regression coefficients have consistently approached 0.6), while PEU has shown a less consistent effect (Venkatesh and Davis, 2000). Based on the universality of the PU construct and its consistency in influencing technology acceptance, we posit (Figure 1): H1 PU will have a positive effect on intention to adopt SNM by SMEs. In the SNM context, it appears that PEU is not a relevant predictor of SNM adoption. PEU construct was traditionally connected to computer efficacy and reflected the degree of technical skills and effort deemed necessary to use a new technology. The fact that social networks websites were developed for mainstream users renders their technical utilisation intuitive and user-friendly. Therefore, no substantial technical effort appears to be required from a small business adopter of SNM to use these sites. In addition, social networks websites are hosted and maintained by third parties that facilitate their use by businesses and provide necessary technical support. Since the majority of small and medium companies are still at the testing stage of this technology, the realistic assessment of other skills (marketing, PR, customer service) needed for SNM to succeed may not be possible. Therefore, we do not hypothesise any effects for PEU on either PU or intentions to adopt SNM. Multiple studies have attempted to extend TAM to include factors that may affect PU for specific technologies and business environments. One of the most frequently proposed determinants of PU has been SI, defined as a user’s perception that important people think the user should adopt the technology (Venkatesh and Davis, 2000). The rationale for SI – PU – intentions link is based on the notion of internalisation, whereas the user incorporates an important referent’s belief into his/her own belief structure (Kelman, 1958) as evidence about reality. The internalisation component of SI has been compared to French and Raven’s (1959) expert power, when the user’s perception of the technology usefulness increases based on persuasive social information. In the SNM context, due to the lack of measurement metrics or positive bottom line results from the companies that have adopted this marketing technology, PU appears to be strongly determined by SI. Professional and mass media regularly emphasise the magnitude and growing importance of social networks, and numerous marketing gurus explain the potential advantages of getting involved with social media. In addition, various success stories and case studies about companies that have creatively used social networks to achieve sales goals penetrate the information space. While some negative information about ‘social media hype’ is also present, experts and authors overwhelmingly agree that using social networks for marketing presents great potential provided businesses find their niche and formulate their goals correctly. Thus, we propose that internalisation effect exists whereas SI positively affects PU in the context of SNM (Figure 1). H2 SI will have a positive effect on PU of SNM by SMEs. In addition to the indirect effect, SI has also been proposed to influence intention directly, through the mechanism of compliance (French and Raven, 1959; Kelman, 1958). Compliance occurs when the user believes that a social referent has the ability to reward or punish the adoption behaviour, and is influenced by the referent’s opinion even without accepting or internalising this opinion. Empirically, while Davis et al. (1989)
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found that SI does not have a significant effect on intentions to use new information systems over and above PU and PEU, Taylor and Todd (1995) found a significant direct effect of SI on intention. In addition, SI has been shown to affect the adoption and use of new media (Webster and Trevino, 1995) and adoption of new technology in education (Robinson, 2006). In the study of broker workstations adoption, Lukas and Spitler (1999) found that SI is a stronger predictor of intended use than PU or PEU. Finally, Venkatesh and Davis (2000) confirmed both direct and mediated by PU effects of SI on intention to adopt varied business process IT systems. In the social media context, businesses may be compelled to use SNM because their customers and other stakeholders use online social networks and expect being communicated to through this medium. Thus, businesses may feel pressured to create their own fan pages even if they have not developed SNM goals or strategies, and are not fully convinced in this technology’s effectiveness. Based on the above, we hypothesise (Figure 1): H3 SI will have a positive effect on intention to adopt SNM by SMEs. The role of SI in adopting a new technology has been suggested to vary depending on the degree of experience with the technology (Venkatesh and Davis, 2000). It is theorised that at the early adoption stages, when knowledge about the technology is low, opinions of experts and stockholders are more influential. After the technology has been implemented, and when its strengths and challenges are better understood, the role of SI subsides (Hartwick and Barki, 1994). Thus, Hartwick and Barki (1994) found that SI effect on intention became insignificant three months after an information technology implementation. Venkatesh and Davis (2000) reported that the influence of social factors was significantly moderated by experience, decreasing both one and three months after a new business technology implementation. Due to the lack of metrics for ascertaining strengths and weaknesses of SNM, and uncertainty regarding the length of its effects on building brand awareness and brand attitude, we theorise that SI will remain a major influencer of intentions to adopt until results assessment and comparability are available for the industry. In addition, once a business has established its social networks presence and in the absence of objective performance indicators, compliance with customer expectations may be the most important factor driving the continuation of SNM use. Thus, those businesses that have had friends and fans following the company on the social network for a long time, may feel obligated to continue SNM to avoid negative repercussions (Figure 1). H4 The positive direct effect of SI on intention to continue using SNM by SMEs will increase with experience. Figure 1
Applying TAM to SNM adoption by SMEs
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Adoption of social networks marketing by SMEs
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Method
4.1 Procedure Business executives of small and medium size companies in the Midwest who attended the 2009 Annual Internet Marketing Conference sponsored by a Midwest university were requested to fill out a paper-and-pencil survey about their experiences with, and plans for utilising SNM (Appendix). Two versions of the survey instrument (for SNM adopters and non-adopters) were distributed to the attendees. Both versions contained demographic and psychographic questions about the company, respondent’s position and functional area, and questions about reasons for adopting and possible benefits of SNM. They were followed by the TAM scale questions adapted to reflect the differences between those who were using SNM and those who were considering its adoption.
4.2 Sample Out of 110 executives in attendance, 65 (59%) returned completed surveys. Due to the exploratory character of this pioneering study, the sample size was deemed acceptable for the purpose of detecting the phenomena of interest (and not for predicting or generalising purposes), given the representative nature of the sample. Respondents represented a wide variety of industries (Table 1), including consumer and business services, business-to-business manufacturing, distribution, and retailing, with 80% reporting annual revenues of less than $25 million (qualifying for the revenue-based SME definition). A great majority (80%) of the respondents held decision-making positions of owner, upper-, or middle-manager in their companies, which made them appropriate subjects for testing TAM. Over 83% represented functional areas of marketing and information technology that are mainly related to adoption and use of SNM. About one-third (33.8%) of the sample were using SNM at the time of the conference, with the remaining 66.2% admitting they had never used social networks for marketing before. Table 1
Characteristics of the sample
Primary business, %
Annual sales range, %
Position in company, %
Functional area, %
Consumer service provider
38.5
Less than $1 32.3 million
Middle management
38.5
Marketing and sales
72.3
B2B manufacturer
18.5
$1.01 to $10 30.8 million
Upper management
35.4
Operations
12.3
Business service provider
15.4
$10.01 to $25 16.9 million
Owner
6.1
IT
10.8
Distributor
12.3
Business research
5
Other
4.6
Consumer brand manufacturer
7.7
Other
15
Retailer
6.2
More than $25 million
20
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4.3 Measures The TAM scales for PU, PEU, intention to adopt a technology (Davis, 1989; Davis et al., 1989) and the social influence scale (Taylor and Todd, 1995; Venkatesh and Davis, 2000) were adapted to reflect the differences between SNM adopters and non-adopters. The experience with SNM question “When did you start using SNM?” was only offered to SNM adopters. Non-adopters’ version contained the question “When did you learn about SNM?” in its place. Additional questions asked about reasons for SNM adoption and its benefits, as well as what social networks sites respondents considered for SNM use or were currently using (see Appendix). Descriptive statistics of main constructs are provided separately for adopters and non-adopters in Table 2, and construct correlations and covariances for the whole sample – in Table 3. Table 2
Descriptive statistics for main constructs # of items
Construct
Range
Mean
Variance
Cronbach’s alpha
1.025 1.032 1.047 1.31 1.389 0.997 N/A
0.92 0.935 0.91 0.868 0.867 0.833 N/A
PU whole sample SNM adopters SNM non-adopters Social influence whole sample SNM adopters SNM non-adopters Experience: adopters
3 3 3 3 3 3 1
PEU whole sample
3
4 (1 to 5)
3.33
0.911
0.897
SNM adopters
3
4 (1 to 5)
3.3
1.364
0.944
SNM non-adopters
3
4 (1 to 5)
3.34
0.642
0.833
Intention to use whole sample
2
2.17
0.814
0.936
SNM adopters
2
2.52
0.58
0.972
SNM non-adopters
2
2.67 (0.67 to 3.33) 2.67 (0.67 to 3.33) 2.67 (0.67 to 3.33)
1.94
1.002
0.882
Table 3
4 (1 to 5) 2.95 3.67 (1 to 4.67) 2.88 4 (1 to 5) 3 4 (1 to 5) 2.8 4 (1 to 5) 3.29 3.67 (1 to 4.67) 2.45 3 (less than 1 yr. to Median between 4 and 5 yrs.) : less than 1 yr
Correlation-covariance matrix: whole sample
PU Social influence Intentions to use PEU
PU
Social influence
Intentions to use
PEU
1.025 0.612 0.526 0.168
0.518** 1.31 0.877 0.163
0.563** 0.823** 0.814 0.165
0.171 0.151 0.191 0.911
Notes: Correlations are above, and covariances – below the diagonal line containing variances. **Correlation is significant at the 0.01 level (two-tailed). *Correlation is significant at the 0.05 level (two-tailed).
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Data analysis and results
Initial examination of the data revealed that the average adoption intention (intention to continue using SNM in the case of companies already utilising this technology) is rather low: 2.17 (var = 0.8) out of five, confirming the apprehensions companies may have regarding this new marketing tool. When compared, the adopter group displayed a significantly higher intention to continue using SNM (mean = 2.52) than the non-adopter group - to adopt SNM (mean = 1.94, F = 5.857, p = 0.019). Consequently, the hypotheses regarding the drivers of SNM adoption were tested separately for the adopter and non-adopter groups. The results revealed that different mechanisms explain SNM acceptance by small and medium companies that have not used this technology before and the intention to continue using SNM by companies currently utilising this marketing tool (Tables 4 and 5). The regression analyses with intentions to adopt/continue using SNM (IA) as the dependent variable and PU, PEU, and SI as independent variables confirmed non-significance of PEU for either adopting (β = 0.1, p = 0.39) or continuing to use (β = 0.2, p = 0.89) SNM by SMEs. However, mean values for PEU [3.34 (sd = 0.8) and 3.3 (sd = 1.2) respectively] do not support our assumption that companies perceive SNM easy to use because they overwhelmingly consider this technology effortless. Even though social networks are hosted and maintained by third-party companies and are supported by their site maintenance staff, relatively low values for PEU in both groups may reflect the respondents’ beliefs that using SNM requires additional skills and effort. For example, a recent survey of senior level marketers showed that responsibility for social media is expected to span a number of departments within an organisation, requiring joint effort of marketing, PR, customer service, research, and IT functions (Internet Advertising Bureau, 2010). Thus, once the decision to adopt SNM is made, cross-functional teams may have to be created, contributing complementary knowledge and skills that already exist in the company. Thus, although the perception of ease of SNM use may be relatively low, this does not reduce the intention to adopt SNM due to the expectation that existing company resources can be synergistically employed for its purpose. The fact that PEU does not affect either the intention to adopt or the intention to continue using SNM may also be explained by the presence of other, more significant drivers of the adoption choice that outweigh the perceptions of ease of use. Our further analysis supports this explanation. Separate regression analyses were conducted for non-adopter and adopter groups to identify the drivers of SNM acceptance and intention to continue its use, respectively. The PEU variable was removed from these analyses based on the above insignificant results. Our findings show that for companies that have not yet adopted SNM, both PU (β = 0.414, p = 0.009), and SI (β = 0.516, p = 0.001), were strong predictors of IA, supporting Hypotheses 1 and 3 (Table 4). Further, PU was found to mediate the influence of SI on AI, supporting Hypothesis 2 (Sobel test statistic = 3.586, p < 0.001). The mediation was partial, since SI and PU were both statistically significant in predicting IA (Table 4). For the adopter group (Table 5), the only significant variable affecting intention to continue using SNM was SI (Hypothesis 3 supported). In order to test Hypothesis 4 and to assess the role of experience in the SI – IA link, we conducted a separate moderated regression for the adopter group with SI, Experience, PU, and SI*Experience as independent variables, and the intention to continue using SNM as dependent variable
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(Table 5). Our results supported Hypothesis 4: longer experience with SNM strengthened the effect of SI on the intention to continue using it (β = 0.763, p < 0.001). Table 4
Drivers of intention to adopt SNM by SMEs not currently using the technology
Dependent variable: intention to adopt SNM Independent variables
B
Std. error
Beta
t
p
(Constant)
0.036
0.276
PU
0.307
SI
0.405
0.13
0.898
0.109
0.4
2.825
0.009
1.66
0.111
0.516
3.641
0.001
1.66
SS
df
Mean square
F
Sig.
28.4
< 0.001
R
0.828
R square
0.686 Regression
12.51
2
6.255
Adjusted r square
0.662
Residual
5.727
26
0.22
Std. error of the estimate
0.47
Total
18.238
28
VIF
Mediation of SI by PU in the decision to adopt SNM by non-adopter firms Regression 1: Dependent variable: PU Independent variables
B
Std. error
(Constant)
1.441
0.395
Social influence
0.651
0.15
Beta 0.635 Sum of square
t
p
3.65
0.001
4.35
< 0.001
df
Mean square
F
Sig.
18.92
< 0.001
R
0.635
R square
0.403 Regression 12.665
1
12.665
Adjusted r square
0.382
Residual
18.746
28
0.669
Std. error of the estimate
0.818
Total
31.411
29
VIF 1
Regression 2: Dependent variable: intention to adopt SNM Independent variables
B
Std. error
Beta
t
(Constant)
0.483
0.251
Social influence
0.605
0.095
1.92
0.65
0.768
6.34
< 0.001
Sum of square
df
Mean square
F
Sig.
Regression 10.842
1
10.842
40.25
< 0.001
0.269
R
0.768
R square
0.59
Adjusted r square
0.575
Residual
7.543
28
Std. error of the estimate
0.519
Total
18.385
29
Note: Sobel test statistic = 3.586, p = < 0.001
p
VIF 1
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Adoption of social networks marketing by SMEs Table 5
Drivers of intention to continue using SNM by SMEs currently using the technology
Dependent variable: intention to continue using SNM Independent variables
B
Std. error
Beta
t
p
VIF
(Constant)
0.086
0.42
0.205
0.84
PU
0.068
0.146
0.069
0.464
0.648
1.399
SI
0.68
0.126
0.8
5.415
< 0.001
1.399
Sum of square
df
Mean square
F
Sig.
22.55
< 0.001
R
0.839
R square
0.704 Regression
14.81
2
7.405
Adjusted r square
0.672
Residual
6.241
19
0.328
Std. error of the estimate
0.573
Total
21.051
21
Moderation of SI by experience in the decision to continue using SNM by adopter firms Dependent variable: intention to continue using SNM Independent variables
B
Std. error
(Constant)
0.572
0.648
PU
0.025
0.152
SI
Beta 0.025
t
p
VIF
0.882
0.39
0.162
0.873
1.525
0.15
0.2
0.87
0.736
0.465
2.227
Experience
–0.146
0.148
–0.142
–0.983
0.338
1.33
Experience*SI
0.216
0.043
0.763
5.002
< 0.001
1.49
Sum of square
df
Mean square
F
Sig.
15.33
< 0.001
R
0.848
R square
0.719
4
3.782
Adjusted r square
0.672
Residual
5.922
18
0.329
Std. error of the estimate
0.574
Total
21.051
22
Regression 15.128
Additional questions about the benefits the companies expect to obtain from utilising SNM, the SNM tactics they would employ, and the reasons they are interested in this marketing technology complement our result. The single most prominent tactic all the respondents selected was creating their company’s account on a social networks site and inviting followers. There was no significant difference in types of benefits that adopters and non-adopters expected from SNM. The benefits most frequently named by both groups include: increasing brand awareness, spreading marketing message, and obtaining customer feedback. Finally, non-adopters significantly outnumbered adopters in naming the following reasons to join SNM: to try a new approach (chi-square = 15.665, p < 0.001), to be an early player in the social networks medium (chi-square = 3.049, p = 0.08), and to better reach our target market (chi-square = 5.682, p = 0.017). As can be seen from the above responses, the major impetus to utilise SNM by SME respondents in
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our sample is of exploratory nature, and is consistent with our finding of SI playing a major role as a driver of SNM adoption and intention to use.
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Discussion
According to our findings, social influence by experts, customers, and competitors affects company intentions to adopt SNM both directly, and through the PU of SNM. Our findings echo earlier results by Venkatesh and Davis (2000) who found that social pressures exert both a significant direct effect on usage intentions over and above PU and PEU, and an indirect effect on intentions mediated by PU. Our results also support Lukas and Spitler’s (1999) found that the role of normative pressure in the intent to use information technology is more important than perceptions about ease of use and usefulness. For those SMEs already using SNM, SI appears to be the only strong determinant of the intention to continue employing this marketing technology, with the amount of experience with SNM strengthening this relationship. This result may be explained by the relative newness of SNM that triggers massive publicity in professional publications, industry circles, and in media, leading to the ‘bandwagon pressure’ (Pangarkar, 2000). The bandwagon theory argues that firms tend to imitate their rivals regardless of value-enhancing consequences for themselves. This happens in the environments characterised by ambiguity of costs and benefits assessment and/or stockholder influences, provided the firm has sufficient resources to support the imitation. In these conditions, the number of rival firms adopting a new technology would serve as a proxy for the cost-benefit, means-ends, or environmental risk indicators (Abrahamson and Rosenkopf, 1993). Since SNM is not considered capital- or labour-intensive, and because its outcomes are still difficult to ascertain, many companies may plan to continue using it for the sole reason of keeping up with their competitors. This supposition is supported by the finding that the longer a company in our sample has been employing SNM, the stronger the influence of social pressure from customers, competitors, and experts on the intention to continue its use. Although our result contradicts Venkatesh and Davis (2000) who found a negative effect of one- and three-month experience on the social influence – intention to continue using a technology link for mandatory technology use context, this difference emphasises both the voluntary nature of SNM adoption and the newness of the SNM technology that amplifies environmental ambiguity and mitigates outcome evaluation. According to Gartner Inc. (Fenn et al., 2009), any emerging technology follows a typical adoption path from over-enthusiasm through a period of disillusionment to an eventual understanding of the technology’s relevance and role in a market or domain. Each phase in this ‘hype cycle’ is characterised by distinct indicators of market, investment, and adoption activities. Thus, Twitter is considered to have ‘tipped over the peak’ of early adoption, and to be about to enter the infamous ‘trough of disillusionment’ characterised by negative press and failures (Fenn et al., 2009). In Gartner estimates, the period from sliding into the ‘trough’ to ‘climbing the slope’ (understanding the technology), to ‘entering the plateau’ (majority adoption) for this technology may take from two to five years. From this estimate, SNM technology usefulness for businesses will not be objectively evaluated for some time. With firms in our sample having had on average less than one year experience with SNM, it appears that SI from the press, experts, and customers will only increase as the experience with SNM use increases.
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Conclusions and implications
With the social media penetrating the business world at an increasing pace, it is important to understand the underlying reasons for companies to adopt SNM technology and to develop strategies and guidelines for using it productively. The existing TAM does not adequately explain SNM adoption due to TAM’s focus on more technical side of technology acceptance, and lack of socially-determined variables in the model. This paper extends TAM in the context of SNM adoption by SMEs. Our findings show that adoption of new and emerging technologies is strongly influenced by SI from experts, competitors, and customers. These SI affect intention to adopt a new technology both directly, and by affecting the perceptions of the technology usefulness. Due to certain amount of ambiguity surrounding the assessment of new technology effectiveness, ‘bandwagon pressures’ may serve as proxies for cost-benefit, means-ends, and environmental evaluation, thus making SI the strongest determinant of intentions to adopt. By following the ‘hype cycle’, companies that have adopted new technologies, continue to be influenced by social pressure as they move from the peak of adoption (characterised by maximum media hype) through the slope of disillusionment (with negative media intensifying) to the plateau of mass adoption, at which point objective assessment of technology effectiveness becomes possible. Based on the above analysis, SME managers facing the decision to adopt or continue using SNM should carefully balance the evidence to estimate how much their decision is justified by a strategic goal vs. the bandwagon pressure, and whether the PU of SNM for the firm stems from hard data or from anecdotal media accounts. In the absence of generally recognised predictive metrics, in order to accurately ascertain the effect of each social media marketing effort for their company, managers should set specific goals and utilise appropriate metrics for their assessment. For example, if a Facebook branding page is created to engage existing customers and reinforce their loyalty, its effectiveness may be measured with online customer surveys, frequency and intensity of their interaction on the page, and a net promoter score measuring the intention to spread positive word-of-mouth. Similarly, a Twitter account established to tackle customer service and PR issues should be gauged by measuring online ‘buzz’ and ‘retweets’. Unique company communications needs should determine the purpose and tactics for social media marketing, as well as the suitable metrics to ascertain its value. While undeniable competitive advantages exist from being an early player, they can only be achieved by following specific objectives, integrating SNM into your overall marketing communications plan and monitoring the results by the means available. Presence in the social media that is not supported by solid long-term strategy may damage the brand by making it vulnerable to uncontrolled viral communications.
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Limitations and future research suggestions
This paper contributes to the existing literature on technology adoption by clarifying the importance of incorporating social elements into models of new technology adoption, and by providing a tentative explanation to the role of experience in ‘social influence – intention to adopt’ relationship. However, its results should be generalised with caution due to relatively small sample (65 executives of small and medium Midwest companies). Further research with a bigger and more diverse sample of companies is needed for our
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conclusions to be extrapolated to the general SME population. Future research should also consider a longer temporal dimension of new technology adoption both in terms of its drivers, and the potential for a curvilinear effect of SI on adoption decision. Due to the viral characteristics of social media, influences by customers, competitors, and marketing experts on companies’ decisions to adopt and continue using SNM tools may manifest differently compared to diffusion processes of other innovative technologies. The function and length of experience with new technology and its effects on the decision to continue using the technology also presents an interesting area for future research. Since social media presuppose customer co-creation, the content of social network brand pages may represent significant brand equity, thus imposing certain switching cost and the need to continue maintaining the account. Finally, different types of social influence (internalisation vs. compliance) may affect technology adoption decisions differentially as the technology matures and the length of company experience increases. Another promising area of research involving a longitudinal investigation may be ascertaining the role of order of entry into social media marketing in determining operational and financial performance of a firm. While generally first-mover advantages are based on preemption of scarce resources and high buyer switching costs, relatively low entry barriers to social media marketing may mitigate this advantage, rewarding late-movers who base their decisions on available evidence of effectiveness.
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Appendix Internet marketing conference participant survey: non-adopter version Screening question: Does your company currently employ SNM? 1
What is your primary business? a Consumer brand manufacturer b B2B manufacturer c Distributor d Retailer e Consumer service provider f Business service provider g Other __________________________________
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What is the annual sales range of your business? a Less than $1 million b $1 million to $10 million c $10.1 million to $25 million d More than $25 million
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What is your position within the company? a Upper management b Middle management c Owner d Other ____________________________________
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What is your functional area? a Marketing and sales b IT c Operations d Other _____________________________________
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When did you learn about social networks marketing? a Less than one year ago b Between one and two years ago
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Adoption of social networks marketing by SMEs c Between two and three years ago d Between three and five years ago e More than five years ago 6
What may be the reasons your company would use social networks marketing? Select all that apply. a To reduce advertising expenses b To be an early player in the social networks medium c Because everybody else is using it/ not to appear a technology laggard d To break through advertising clutter e To better reach our target market f To try a new approach g Other ______________________________________
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Please indicate whether you agree or disagree with the following statements regarding your thoughts about SNM. 1 – strongly disagree, 5 – strongly agree. a
I find social networks marketing easy to execute
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Social networks marketing is easy and understandable
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It is easy to become skilful at social networks marketing
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SNM may enable our company to accomplish goals quickly
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Using SNM may increase our productivity and ROI
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Using SNM may enhance our company’s effectiveness
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Our company intends to use SNM on a regular basis
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Our company plans to use SNM
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People important to our company think we should use SN
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It is expected that companies like ours should use SNM
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Our competitors use SNM
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Companies that are best in our industry use SNM
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What social networks would you participate in? Please select all that apply. a Face Book b My Space c Twitter d You Tube e LinkedIn f Community on your company’s website g Other _______________________________
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What are the benefits SNM may provide for your business? Select all that apply. a Increases brand awareness b Spreads marketing message c Enables customers to participate in product/service development
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Provides customer feedback Enables better marketing research Improves customer support Other ______________________________
10 What social networks marketing tactics would work best for your business? Select all that apply. a Creating our own account on a social network site and inviting followers b Creating a brand community/customer forum on our own site c Providing customer reviews and ratings opportunity on our site d Placing advertising on social networks sites f Other _______________________________ 11 What % of your sales may come from SNM? a 1% to 5% b 5.1% to 10% c 10.1% to 25% d More than 25%
