ATP (Áreas Turísticas Protegidas)

Actor Network Theory (ANT) is a highly powerful account within the sociology of science that explains social order not through an essentialised notion of ‘the social’ but through the networks of connections between human agents, technologies and objects (Couldry, 2008). Perceived from a tourism SMMEs’ perspective, ANT would attempt to describe the significance of networks and interactions among various SMME stakeholders (i.e. customers, suppliers, regulators, competitors, investors and community), SMTs and social objects generated through such interactions. ANT seeks to explain social order through the networks of connections between human agents, technologies and objects (Couldry, 2008). In this context, social media are an integral part of ANT, allowing us to better understand human behaviour in the use of technology-mediated social settings which impact groups, communities, institutions and organisations (Shirazi, 2014). The SMMEs’ exploitation of social media platforms such as Facebook, Twitter, etc. could provide a panoramic view of transactive behaviours (e.g., buying, selling, bargaining and social exchanges) of various stakeholders they interact with in the fulfilment of their commercial activities. This view offers an insight into how a technological artefact is deployed through the complex processes of interactions among the parties involved (Lee, Harindranath, Oh & Kim, 2015). ANT helps describe how actors form alliances, enrol other actors, and use non- human actors to strengthen such alliances and to secure their own interests. The theory can, therefore, serve as useful interpretive tool for understanding SMMEs’ collusive behaviour, the formation of strategic alliances, other offensive and defensive mechanisms they employ when dealing with their rivals including large established tourism enterprises.

The actors in the context of this study are individuals (potential customers, tourism SMMEs, their suppliers, investors, financiers etc.), groups, organisations (competitors and suppliers) and government and regulators. Fundamentally, social groups have power if they are able to control the acts and minds of other groups (Shirazi, 2014). It goes without saying that SMMEs can shape the opinions and mould the dispositions of their various stakeholders through SMTs acts such as online advertising, promotions, crowd sourcing and social commentary about products via social media platforms. Shirazi (2014) further states that the actor as an obligatory passing point in a network has power, and thus the more networks the actor has, the more power that actor has over time. In other words, the actor gains more power when she effectively uses the network resources on a large scale. The Actor-Network Theory, therefore, provides a lens through which to view and understand how technology shapes social processes (Cresswell, Worth & Sheikh, 2010).

Pollack, Costello and Sankaran (2013) however, posit that a central quality of an actor is that it acts, resulting in some transformation of something into something else, which may at some point also take action. However, ANT predominantly focuses on tracing networks of associations between actors, building understanding of interaction and organisation without imposing predetermined structure (Pollack, Costello & Sankaran, 2013). Given the highly competitive nature of small tourism businesses in resource constrained contexts and the temptation to devise defensive tactics when confronted with competition from rivals, the pressure to conceal information about tactics may compel SMMEs not to use social media platforms due to fear of rivals emulating their business strategies. Shirazi (2014) further states that all actors in a community (individuals, groups, private and public institutes) interact through the use of social media to share information and develop knowledge in a quest to generate meanings that may result in some sort of socio-cultural, political or economic actions. What Shirazi does recognise is that the social media mediated relationships are not always complementary but can also be competitive and repulsive to collaboration and mutual exchange. From an ANT perspective, the world is full of actors, both human and non- human, any of which could be intermediaries or mediators (Pollack, Costello & Sankaran, 2013). The authors further state that ANT is used to trace the network of connections between actors, who both influence and are influenced by other actors in

an ongoing network of mediation. Action is not seen as independent choice, but rather the result of a diffuse network of influence (Pollack, Costello & Sankaran, 2013). Ghazinoorya and Hajishirzi (2012) concur that these actors can be an authority that either influence and use others or have no motivation and will be under the control of other actors. Ghazinoorya and Hajishirzi (2012) posit that, generally, ANT conceptualizes social interactions in networks.

3.5.2. Theory of SMTs in relation to entrepreneurship

3.5.2.1. Unified Theory of Acceptance and Use of Technology model (UTAUT) This model was developed based on social cognitive theory and a combination of eight prominent information technology acceptance research models (Taiwo & Downe, 2013). According to Wu, Tao and Yang (2008) the UTAUT, integrates the issues that are mentioned in the relevant documents into four main core determinants: Performance Expectancy (PE), Effort Expectancy (EE), Social Influence (SI), Facilitating Conditions (FC), and four variables, which are gender, age, experience and voluntariness of use. Equally, UTAUT claims that three main core determinants (performance expectancy, effort expectancy, and social influence) determine the intention toward using a new technology while facilitating conditions and the behavioural intention toward using relate to the user behaviour (Armida, 2008). Venkatesh, Thong, and Xu (2012) assert that UTAUT has distilled the critical factors and likelihoods related to the prediction of behaviour intention to use a technology primarily in organisational contexts. Furthermore, the authors state that this model has served as a point of departure and has been applied in both organisational and non- organisational settings.

According to Venkatesh et al, (2012) most studies using UTAUT employ only a subset of the concepts, particularly by dropping the moderators. Venkatesh et al, (2003) posit that the core determinants play a significant role as a direct determinants of user acceptance of and behaviour in technology contexts. They have an influence on the behavioural intention and therefore actual system use.

Mandal (2012) posits that UTAUT is the most dominant adoption theory that explains nearly seventy per cent of variance in adoption behaviour. In accord, Moghavvemi et al. (2012) add that this model was developed to measure individual business

characteristics toward the intention to use new technology in an existing business. Therefore, this model can be used by entrepreneurs to adopt social media technologies in their businesses. Furthermore, the theory can be used to explain and predict tourism SMMEs’ utilisations and intentions to use SMTs. For example, in 2012 Mandal used this model to explain social media adoption by microbusinesses and Moghavvemi, Salleh, Zhao and Mattila (2012) used the model in their study to test IT innovation and adoption by entrepreneurs. According to Benbasat (2007), the most important streams of social technologies research is the understanding of individual business’ acceptance and use.