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The Relationship Between Marketing Communication Constituents, Perceived Benefits and Information System Adoption Malliga Marimuthu, Universiti Sains Malaysia;
[email protected] *Siva Muthaly, Swinburne University of Technology;
[email protected]
Abstract The influence of marketing communication in decision making is not a new idea, however, the impact of marketing communication constituents on drawing business customers’ attention and intention towards information system (IS) adoption has not been widely studied. The current paper develops and empirically tests the potential relationship between marketing communication constituents, perceived benefits and IS adoption. The study suggests that marketing communication impact should be investigated by considering the effect of several marketing communication constituents for sustainable IS adoption. Empirical results from the study of IS adoption among retailers in Australia, confirms that marketing communication constituents are imperative in enticing business customers’ perception and intention towards IS adoption. The paper concludes with implications of the study for theory and practice. Keyword: marketing communication, retailing, information system adoption
Dr. Malliga Marimuthu Senior Lecturer in Marketing School of Management Universiti Sains Malaysia, Malaysia Penang 11800 Tel: +604 6532753 Email:
[email protected]
Asso Prof. Siva Muthaly (PRESENTER) Head of Marketing & International Studies Faculty of Business and Enterprise Swinburne University of Technology BA1125, PO BOX 218 Hawthorn , Victoria 3122, Australia Tel: 613 9214 5885 Email:
[email protected]
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The Relationship Between Marketing Communication Constituents, Perceived Benefits and Information System Adoption Introduction Marketing communication is a systematic approach by a business to communicate its offerings and to stimulate a particular perception of products and services in its target market (Orlander and Sehlin, 2000; Smith et al., 1998). In the context of technology adoption, marketing communication is defined as any message that is transmitted by the sellers to prospective buyers that may influence buyers’ awareness and knowledge about the technology and their adoption decisions (developed from Clemente 1992; Herriott 1997). There are only a small number of empirical studies that have explored the relationships between marketing communication and technology adoption (Mahajan, Muller et al. 1990; Lee, Lee et al. 2002). These studies have highlighted the positive effect of marketers’ communication on individual consumers’ intention to adopt the technology. Lee et al. (2002) found that the significance of communication constituents (source and modality) vary across different segments of adopters. This study addresses the gap in the relationships between marketing communication and technology adoption intention. The current study examines the influence of various marketing communication constituents on IS adoption among retail business. Three constituents of marketing communication are studied in the study, namely channel used, content, and context of the message. The aims of this study are two folds. The first aim is to better understand the influence of marketing communication constituents on perceived benefits and behavioural intention of potential users to adopt IS. Due to dearth of research in this area, there is very poor understanding of how these factors interplay. The second aim of the study is to unveil the significance of perceived benefits as mediator for the relationship between communication constituents and IS adoption. Drawing from the IS adoption literature, this study extended the models explained technology adoption (theory of reasoned action, theory of planned behaviour, technology acceptance model) by including the marketing communication constituents as a measure of cognitive response and behavioural response. Figure 1 illustrates the proposed integrated conceptual model. This study proposes three marketing communication constituents as predictor of IS adoption, i.e. channel used, content, and context of the message. The proposed marketing communication constituents were identified and developed based on literature review. Chakrabarti et al. (1983) defined communication channel as means by which information is moved from one point to another (e.g., internet, salesperson, telephone). Content of communication was defined as the characteristics (e.g. credibility, relevance, clarity and timeliness) of the message being communicated (Merchant, 2000). While context of the message was defined as and the format (e.g., text, audio, graphic) by which the message is conveyed (Hoffman and Novak, 1996). In general marketing communication is recognised as an instrument to sell products and services (Heinonen and Strandvik 2005). According to Amoako-Gyampah and Salam (2004), effective communication seeks to influence the receiver’s knowledge, attitude and behaviours. Thus, the current study believes that communication exposure via appropriate communication constituents can help stimulate business customers to adopt the advertised IS.
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Figure 1: Conceptual Model Guiding the Study
Communication Channel
Communication Content
Perceived Benefits
Behavioural Intention
Communication Context
The above discussion leads to the following main hypothesis: H1
:
H2
:
H3
:
H4
:
There is a significance relationship between communication channel and (1) perceived benefits and (2) behavioural intention. There is a significance relationship between communication content and (1) perceived benefits and (2) behavioural intention. There is a significance relationship between communication context and (1) perceived benefits and (2) behavioural intention. Perceived benefits mediate the relationship between communication constituents and behavioural intention.
The cognitive response of the potential users are measured through perceived benefits variable. Perceived benefits affect technology adoption in term of the perceived ease of use and/or perceived usefulness of the technology. Perceived benefits have consistently been found to be an important predictor of adoption intention (Rice and Webster, 2002, Syed Shah Alam, 2009). If a potential user does not perceive the technology in a positive way, he/she will be reluctant to adopt the technology. Behavioural intention to adopt was defined as strength of organisation’s intention to use the technology in the future (Taylor et al., 1995).
Method The population of the study are the retailers in Australia. The choice of retail industry was made due to the nature of technology, geographical information system (GIS) selected for the study. Managers from large and medium size retail organisations were targeted. Overall, 135 surveys were received from the 1000 medium and large sized retailers (13.5% response rate). Out of that, completed usable questionnaires (112) were received from senior managers who were all non-users of the IS. The sample size is considered satisfactory because the study targets business respondents where it is generally more difficult to obtain a large response. The average range of response for studies targeting top management is 10% to 15% (Thong 1999; Riemenschneider, Harrison et al. 2003; Grandon and Pearson 2004) The survey contained total of 30 items. The questionnaire items were adopted from different sources. The scale for the communication channel consisted of seven items (i.e. face-to-face as one-to-one, face-to-face as group, direct mail, published literature, telephone, internet as 2
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informational communication and internet as interactional communication). Communication content was measured using four items (i.e. text, text with graphics, audio and audio plus video). While communication context were measured using eight items (i.e. accurate, complete, realistic, specific, sufficient, up-to-date, personal and relevant). The marketing communication constituents scales were adopted mainly from the International Communication Association (ICA) and some were developed from industrial observation. The scale that were used to measure perceived benefits were selected from technology adoption studies (Robinson et al., 2005; Agarwal and Prasad, 1999 and Lynn et al., 2002) and it consisted of eight items. While behavioural intention were measured using three items adopted from Robinson et al. (2005) and Karahanna et al. (1999). All the items were measured on a 5-point Likert-type scale that varied from 1= strongly disagree to 5= strongly agree. Figure 1 illustrates the conceptual model guiding the study. The model tested the potential retailers’ intentions of using a particular IS, GIS within next six months. GIS is a computer assisted system to capture, store, analyse and display spatial data. GIS is widely applied in the retail industry for performing functions such as market analysis, store site selection, marketing and advertising strategy, inventory management, service vehicle routing and customer care (ESRI 2006; MapInfo 2006). The data collected via the online survey were analysed using partial least squares (PLS). This choice was made based on the suitability of PLS to analyse the model, its ability to analyse complex and predictive model, small sample size and residual distributions. Partial Least Squares (PLS) is utilised to examine the goodness-of-fit of the research model, and to test the strength of the proposed relationships in the research questions. Results and Discussion The hypothesised model was estimated using PLS. The measurement model in PLS is evaluated by examining the individual loading of each item, internal composite reliability (ICR), average variance extracted (AVE) and discriminant validity (Chin 1998; Compeau, Higgins et al. 1999). Table 1 provides results of the PLS measurement model. The structural model in PLS was assessed by examining the path coefficients and t-statistics. R2 was used to indicate the strength of the predictive model.
Table 1: Reliability, Convergent and Discriminant Validity
Channel Content Context P_Benefits B_Intention
channel Context Content P_Benefits B_Intent ICR .90 .78 .92 .61 .85 .95 .51 .67 .84 .94 .18 .17 .16 .86 .51 .48 .41 .15 .93 .94
AVE .61 .73 .71 .74 .88
In the current study, the proposed model explained 34% of the variance in behavioural intention. Among the three marketing communication constituents, communication channel indicated the strongest significant affect on perceived benefits and behavioural intention at the significance level of 0.001 respectively. While other two marketing communication constituents, communication content and communication context which significantly affect
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perceived benefits at the level of 0.05 and 0.1 respectively did not show any significant affect on behavioural intention. Perceived benefits indicated significant affect on behavioural intention at the significance level of 0.05. Without the marketing communication constituents, the cognitive variable which is perceived benefits of the technology explained only 7.6% of the variance in behavioural intention. The size of effect of marketing communication constituents compared to perceived benefits can be determined based on R2 change and the effect size (Bollen and Paxton 1998; Chin, Marcolin et al. 2003). The changes in R2 of 0.26 and effect size of 0.40 between the model included and model excluded marketing communication constituents indicated a large effect of marketing communication constituents in business customers’ pre-adoption decisions towards technology based on the guideline recommended by Cohen and Cohen (1983). In sum the study confirmed that marketing communication constituents including communication channel, communication content and communication context significantly affect business customers’ perceived benefits of technology which later stimulate their intention to use the technology. Mediating effect aims to measure the existence of significant intervening mechanisms between independent variables and the dependent variables. This study test the mediating effect of perceived benefits between the relationship of three marketing communication constituents and behavioural intention to adopt the GIS. The study adopt the approach suggested by Baron and Kenny (1986) to test the mediation hypotheses. In this study, mediation testing procedures only reveal partial mediation since the independent variable (marketing communication constituents) still shows some effect on the dependent variable (behavioural intention) after including the perceived benefits. That is, the path between independent and dependent variables still shows a significant effect at 0.05 level with the presence of the proposed mediating variable. Further analysis involving direct, indirect and total effects was carried out to confirm the size of the mediating effect as proposed by Mackinnon (1995) and Shrout and Bolger (2020). Table 2 summarises the direct, indirect and total effects for mediators. Perceived benefits showed the highest mediating effect with total of 0.63 for marketing channel, followed by the effect for marketing context and marketing content. In sum, perceived benefits significantly mediate the relationship between marketing communication constituents and behavioural intention towards adoption. Table 2:
Direct and Indirect Effects of Mediating Perceived Benefits
Independent Marketing Channel Marketing Channel Marketing Context Marketing Context Marketing Content Marketing Content
Intervening
Dependent
non
Behavioural Intention Behavioural Intention Behavioural Intention Behavioural Intention Behavioural Intention Behavioural Intention
Perceived Benefits non Perceived Benefits non Perceived Benefits
Direct effect 0.53
Indirect effect na
Total effect na
0.57
0.06
0.63
0.48
na
na
0.45
0.48
0.48
0.41
na
na
0.37
0.41
0.41
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Note: Refer to Figure 5.7 Indirect effect = (a) x (b), Direct effect = (c), Total effect = direct effect + indirect effect.
Conclusion The implication of this study on theory is mainly on expanding the literature review by including communication constituents. The outcome of the study demonstrates that, the inclusion of marketing communication constituents into the conceptual model improves the model fit. It can be interpreted that marketing communication constituents play an important role in creating an awareness of benefits for the use of technology and enhancing business customers’ intention to purchase new technology. Using retailers in Australia as research setting, this study found that marketing communication constituents (communication channel, communication content and communication context) are relevant in influencing potential users to adopt the IS technology as to improve the retail analysis, retail operations and retail strategies. The relationship between marketing communication constituents and adoption is improved by perceived benefits which act as mediator. Overall the predictor and mediator relationship of marketing constituents demonstrated in the model adds value to the body of knowledge in the field of technology adoption intention as persuasive marketing. The outcome of this study has a number of implications on the practitioners and academicians. The study recommends that managers and marketers should understand the important of different communication constituents and perceived benefits in influencing business buyers’ decision of adopting IS. More efforts should be made to plan separate strategies that can utilize the efficacy of various communication constituents in line with the type of technology promoted and customers approached. The actions will lead to increase potential customers perceptions towards the new technology. Overall, the study provides insights for marketing managers on how to plan different strategies and allocate budget for different communication constituents employed in marketing new technologies to the business buyers. In addition, this study provide essential guidelines for future research. Further research should identify other marketing communication constituents (e.g. communication source, communication purpose) that may influence perception and IS adoption decisions. Future research should also test this relationship in other sectors other than retailing, for example banking, education and tourism. This business customers study also can be extended among consumers for different range of products or services.
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