A technology diffusion perspective of geographical information technology across Mozambican institutions

Over the last century, the human race has witness the technology revolution. This revolution is creating a new order in world, the era where information is one of the precious assets for nations and governments. In the coming decades, more is going to change in the technology field than the past century. Natural hazards, floods, tectonic activities, within others that in past many nations have fallen, today it can be predicted, monitored and controlled. Among the most extraordinary types of technologies, geographic information technologies (GIT) is gaining attention over decision makers and top managers of many sectors. These technologies can be described as all sort of computer systems used in processing georeferenced information. Over the years these systems were kept in shadow and ignored by organizations. Mozambique introduced these technologies after independence. Over the years these technologies have mature and expand to a wide range of sectors of activities. In our days, these systems are present in all most every Mozambican institution. The overall goal of this study we intend to contribute to a better understanding of the determinants behind the adoption of geographic information technologies in Mozambican institutions (public, private, NGO’s). To be able to cover the main goal, three studies have been developed. We started in chapter two with geographic information technologies literature and narrow to a specific case study (Mozambican context). In chapter three we analyze the determinants behind geographic information technologies at two stages of adoption (intention and adoption) applied for Mozambican institutions and a research model have been developed. In the third chapter, we propose a research model to understand the determinants behind the geographic information technologies at Post-adoption stage. The combination of innovative theories and frameworks that operates at organization level provides a solid foundation of our study. Two research models have been developed and proposed. The first research model is characterized with seven variables seeking to explain the drivers behind the adoption of geographic information technologies at intention and adoption stages. The variables declared were technology competence, security, financial concerns, competitive pressure, government policies, donor pressure, and intention to adopt. The variables donor pressure and government policies played a key role in motivating organizations to adopt new technologies. In the second research model we declared 10 variables seeking to understand what takes organizations to keep using and increase the level of use of geographic information technologies at post-adoption stage. The variables were relative advantage, compatibility, complexity, organization size, geographic scope, expansion opportunities, coercive pressure, normative pressure, mimetic pressure and GIT use. This work provides several contributions for research, practice, advancement of knowledge, for experts in the field of these technologies, society and institutions. In first paper, the results showed that the main drivers of GIT use by organizations are compatibility, competitive pressure, complexity, donor pressure, government policy, intention to adopt, innovation, relative advantage, security, and technology competence, with compatibility and technology competence being the mains ones. In second paper, technology competence, security, competitive pressure, are important drivers to explain the intention to adopt GIT. Financial concerns, government policies, donor pressure, and intention to adopt are important drivers to explain adoption of GIT. The donor pressure is the only driver that is statistically significant in both intention and adoption of GIT. In the third paper, the variables compatibility, geographical scope, expansion opportunities, and normative pressure contribute to explain the GIT use. The relative advantage, complexity, coercive pressure and mimetic pressure contribute to explain the intention to increase the GIT level of use. The model explains 59.2% of variation in GIT use and 57.0% of variation in intention to increase the GIT level, revealing substantial power of explanation for the GIT post-adoption.