Information and Knowledge Management using ArcGIS ModelBuilder

2. Methodology
Giovanni Camponovo
Relevant papers about motivations in virtual communities were identified through an extensive
literature review whose initial corpus consisted in the articles published after year 2000 in the top ten
journal in the information systems discipline as proposed by the Association for Information Systems
and in particular by the ranking of Rainer and Miller (2005) 1 as well as the main IS conferences (ICIS
and the various regional conferences).
To this corpus, we added other papers we could find through online databases like ACM Digital
Library, ABI Inform, JSTOR, Elsevier and SpringerLink. The search strategy used to identify articles in
those search engines was based on combining relevant keywords like virtual communities (with
variants such as online communities, electronic communities, electronic networks of practice as well
as the various specific types of communities identified thereafter in the paper) and motivation (with
variants like participation, contribution, gratifications and action).
Finally, other references were obtained from this initial corpus by looking at the references cited in the
various papers, with the process being repeated iteratively until no further references were identified.
In this phase we also collected the various papers describing the various general motivation theories
cited in the various articles.
Of all the references collected, we only retained papers proposing empirical studies using primary
data: we considered both qualitative studies (e.g. based on interviews or content analysis) and
quantitative studies (e.g. based on surveys) leaving out purely theoretical papers. These references
were then entered into a reference management software to check for duplications and relevant
papers were classified by type of community and summarized into a spreadsheet containing the
authors, year or publication, methodology, community type, country, reference theories employed, the
various motivations found and their relevance.
3. Literature review
3.1 General motivation theories
Human motivation is a popular theme among researchers in a broad number of disciplines like
psychology, sociology, economics and information systems. Consequently, many theories have been
developed to explain human behaviour and hereafter we briefly illustrate the ones that are most
relevant to our context (that have been used as a basis to explain motivations for participation in
virtual communities).
One early theory is the expectancy-valence theory (Vroom, 1964; Atkinson, 1966), which suggests
that individuals are motivated to do an activity if they expect that their efforts will lead to a good
performance (expectancy), that will lead to desirable outcomes (instrumentality) that are valuable to
them (valence).
A first stream of motivation theories focuses on the determinants of intentional behaviour. The Theory
of Reasoned Action (Fishbein and Ajzen, 1975) suggests that a person’s behavioural intention
depends on his attitude towards the behaviour (i.e. “a function of beliefs about the behaviour’s
consequences and evaluations of those consequences”) and his subjective norm (i.e. his “beliefs that
relevant referents think he should or should not perform the behaviour and his motivation to comply
with the referents”). The Theory of Planned Behaviour (Ajzen, 1991) extends it by adding the
construct of perceived behavioural control to consider “the perceived ease or difficulty of performing
the behaviour”. Building on these two theories, the Technology Acceptance Model (Davis, 1989)
states that intention of using a technology is determined by its perceived usefulness (the belief that it
would enhance one’s performance) and its perceived ease of use (the belief that it would be free of
effort). Finally, the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al.,
2003) combines several of the preceding theories by considering four determinants of intention
(performance expectancy, effort expectancy, social influence and facilitating conditions) and four
moderating variables (gender, age, experience and voluntariness of use). It is worth to notice, that
1 MIS Quarterly, Communications of the ACM, Information Systems Research, Management Science, Journal of Management
Information Systems, Harvard Business Review, Decision Sciences, IEEE Transactions (various), Decision Support Systems,
ACM Transactions on Information Systems and European Journal of Information Systems
599