Adoption of web-based technologies in pursuit of work productivity and creativity within the public sector in South Africa
Notice bibliographique
Résumé
ABSTRACTThis paper reports on the diffusion and adoption of web-based technologies by government departments in KwaZulu-Natal Province in the context of work productivity and creativity. Through a survey, key government departments were sampled through multistage and purposive sampling techniques. Questionnaires that were largely structured were distributed to 260 top, middle and lower management respondents from four government departments in the province, namely, department of Arts and Culture; Home Affairs, Education and Health. The data was analysed using thematic categorisation and tabulation, and the findings were presented descriptively. The study adopted Rogers's theory (Diffusion of Innovations) as its theoretical framework. The results show that essential Web-based tools and services are largely available and accessible to the civil servants. The results further depict that most of the civil servants used the Web to communicate among themselves, to disseminate departmental information, and for research purposes. The respondents largely concur that the use of the Web had increased their work productivity and creativity. It is concluded that despite the constraints and challenges encountered in the application and use of the Web in government departments, a wide range of web-based technologies have been adopted to facilitate the sharing and exchange of information in the sector. Whether levels of Web service availability and accessibility are uniform among the civil servants (both management and ordinary staff) requires further investigation.Key words: web technology, civil servants, World Wide Web, public sector, social informaticsIntroductionThe aim of this paper was to assess the diffusion and adoption of web-based technologies by selected government departments in the context of work productivity and creativity in the KwaZulu-Natal Province. With a total area of 94 361 square kilometres, KwaZulu-Natal is roughly the size of Portugal (South African info, 2012). While it is the country's third-smallest province, taking up 7.7% of South Africa's land area, it has the second-largest population, estimated at 10.6-million people in 2010 (South African info, 2012). The terms Internet and Web are often used interchangeably as the Web is widely considered to be part of the Internet. However, there is a difference between the two. Computers around the world communicate via the Internet. The Web makes that communication a fun activity. Therefore the Internet can best be described as a Network of millions of computers that offers information, communication, and wealth of online activities, while the Web may be regarded as a simple way of accessing, sharing or exchanging information over the medium of the Internet by use of Hypertext Transfer Protocol (HTTP), that is one of the languages spoken over the Internet to transmit data (Mbatha, Ocholla and Le Roux, 2011)In strengthening this view, Malik (2006: 6) and Deitel and Deitel (2005: 5) describe the Internet as an interconnection of Networks that allows computers around the world to communicate with each other. Basically, the Internet allows computers to be connected and communicate with each other. Conversely, the Web uses software programs that enable computer users to view documents on almost any subject over the Internet with click of a mouse. Undoubtedly, the Internet has become one of the world's leading communication mechanisms (Mbatha and Ocholla, 2011; Mbatha, 2012).The study on web technology is relevant to modern development, particularly in Africa, where the needs and use of ICTs is either low or less developed and also where embracing information society and knowledge society as a new way of life is a major challenge (Mbatha, Ocholla, and Le Roux, 2011; Mbatha, 2009: 83). The web has been described by numerous researchers as a catalyst for improving work productivity and creativity, especially in public offices (Carol, 1998; Kling, 2000 and Mbatha, 2009: 83). …
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,006 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».