Abstract
The objective of this article is to present a framework of Tourism Intelligence System (TIS) with support in Knowledge Governance (GovC) to support decision making in tourist destinations. The form of cooperation and use of knowledge should be structured through mechanisms that allow availability and reliability. The methodological framework is structured in Design Science Research (DSR) of technological and applied nature, with data collection method using a qualitative approach, classified as exploratory and descriptive, from the validation of semi-structured interviews with experts in the tourism sector and technology. This architecture was composed of three layers: knowledge application, knowledge generation and application, and knowledge generation. It focuses on the extraction of data generated by the tourist trip in the pre-trip, during trip, and post-trip phases, using Knowledge Management (KM) processes such as knowledge identification, acquisition, and use. The GovC aspect considered the mechanisms aimed at the sustainability and evolution of the TIS, as well as the hybrid structure through network and market formation, by means of knowledge centers with actors involved in the segments of the tourism production chain.
You have full access to this open access chapter, Download conference paper PDF
Keywords
1 Introduction
Each process of formatting a tourism product and visiting a destination generates a quantity of data that should be collected and used by decision makers with the aim of efficiently allocating public resources to increase tourist services and satisfaction, thus making their territory more attractive and competitive. (Soualah-Alila et al., 2016).
Studies and research on tourism governance introduced since the 1990s point to the limitations of public–private partnerships, alliances and business networks, usually focused on the economic and political side, aimed at increasing the competitiveness of the destination. (Erkuş-Öztürk, 2011; Wang & Li, 2013; Butler, 2020).
In turn, the implementation of tourism governance is related to processes and structures such as power sharing in a multilevel, diverse, and decentralized integration, through cooperation networks that allow flexibility in experimentation and knowledge creation in a differentiated way (Trentin, 2017).
With this in mind, the Tourism Intelligence System (TIS) can be a facilitator in sharing information across the destination network, be it experiences, products, services and reviews. This shows that people are increasingly dependent on data to make decisions.
Tourism governance, coupled with knowledge governance, can provide an approach to decision-making and regulation of tourism, bringing more efficiency in the development of policies and programs for the sector. Therefore, this article aims to present a framework for a Tourism Intelligence System with support in Knowledge Governance to support decision-making in tourist destinations.
2 From Tourism Governance to Knowledge Governance
Hall (2011) identified six characteristics related to governance models that bring aspects very adherent to the tourism sector, such as flexibility and revision, diversity and decentralization, and multilevel integration.
These aspects largely align with the principles of the Organization for Economic Cooperation and Development—OECD (2012) and highlight important points to consider in tourism governance, including experimentation and knowledge sharing and multi-level integration.
And the other hand, the complexity governance can be observed by Grande (2012, apud Ysa et al. 2014) describe five key elements which can be identified in governance concepts: (1) new non-hierarchical structure and mechanisms; (2) governing and the criticism of hierarchy as steering principle; (3) emergence of new actors, either private or non-profit; (4) increasing complexity of political actions, and (5) increasing cooperation and collaboration among stakeholders, and this impacts both the governance of tourism and knowledge.
About tourism governance, Bono iGispert and Clavé (2020) define it from the perspective of the actors of the system of a tourist destination, the following aspects: (i) participation, as a form of cooperation and possibility of acting together; (ii) coherence, understood as strategic planning and management; (iii) responsibility, related to the fulfillment of the functions and criteria of sustainable development; (iv) effectiveness, understood as efficiency in obtaining results; (v) know-how and quality, understood as knowledge and training; (vi) openness, related to active communication and transparency, and (vii) simplicity, understood as the ability to provide a response.
Therefore, the definition of the tourism governance model requires a conceptual framework of the platform that combines decision-making structures, collaboration facilitators and operational procedures in order to govern the platform by Tourism Information System—TIS, that is, governance relates to all activities and interactions of governance and trust (Crescencio, 2022).
So, it’s necessary use the TIS to management everything and aim at the process of knowledge management. It can be considered in a general way in five: people (Government, Customer, Citizen, Stakeholders), hardware (planning, architecture), software, data (presentation method) and networks (telecommunications), that is, they are human resources and information and communication technology that need to interact to reach the desired goal within an organizational environment (O’Brien, 2020; Gregersen, 2018), and generating extensive knowledge that will require specific governance.
Knowledge governance comprising of both knowledge management governance and information technology governance whereas knowledge governance is a system that governs important knowledge operational sectors inside the company or groups, tourism governance focuses in the perspective of the actors of the system of a tourist destination (Otowicz et al. 2022).
To De Sá Freire et al. (2017) the KGM list (i) the formation of internal and external partnerships aimed at a culture of transparency; (ii) the formation of intra-organizational and inter-organizational networks through effective communication aimed at reducing cognitive distances and promoting new relationships; (iii) human resources management practices that allow the construction of psychological bonds of trust and sharing for rapprochement and understanding among parties, generating higher levels of empathy; (iv) formal incentives for KM; (v) shared property rights; (vi) promotion of organizational absorptive capacity; (vii) performance measurement and monitoring to control the costs and transaction risks of knowledge production and transfer; (viii) decentralized management coordinated by communities and project teams; (ix) promotion of inclusion for participation and collaboration; and (x) authority and leadership systems whose hierarchy is based on consensus with the social construction of meaning for decision-making.
Finally, the governance mechanisms linked to inter-organizational knowledge make the network organization smarter as a strategic business action used in the context of TIS.
3 Methodology
This article has a methodological framework in Design Science Research (DSR). According to Peffers et al. (2007), the construction of the methodological approach proposed for a DSR is the junction of several consensual elements from authors who essentially agree on the need for them in the process.
The result is understood in six stages, namely: (i) definition of the problem, (ii) definition of the artifact for its solution, (iii) design of the device, (iv) demonstration of the device solving the problem, (v) evaluation of the device, and (vi) communication of the results (knowledge).
Based on Botelho et al. (2011), for the construction of the device it was observed the state of the art of contributions to the development of theories on the concepts addressed in this research: “tourism intelligence system”, “tourism governance”, and “knowledge governance”. The searches were carried out in academic articles found in prestigious databases recognized by the academic community, such as Web of Science, Scopus, and Scielo, as well as the CapesFootnote 1 Theses and Dissertations Bank.
In the databases, 327 publications were identified, in addition to 7 documents from the literature produced by the public and private sectors of tourism.
The third activity, called “Design and Development”, concerns the artifact itself, the creation of the model, method, instances and the designed object, and what it contributes to the research. This step includes determining the desired functionality of the artifact and its architecture.
This step was outlined as a preliminary conceptual framework of a TIS based on GovC, with the idea of relating the concepts obtained from the bibliographic and documentary theoretical survey, in order to identify the elements, processes, mechanisms, and structures necessary for a TIS having as a basis the precepts of Knowledge Governance.
4 Results
Based on the researched theoretical bases, a preliminary conceptual model for a Tourism Intelligence System based on GovC can be reached. Its structure is divided into three layers: Knowledge Generation Layer, Knowledge Generation and Application Layer, and Knowledge Application Layer.
4.1 Knowledge Generation Layer
The analysis of this Knowledge Generation Layer starts with the Customer Journey, in which it is possible to identify the stages of the travel cycle that occur in three moments: i. prospective phase (pre-visit)—searching and planning, reducing decision risk, increasing interest in, building an understanding, during (on-site, the visit)—enhancing convenience and speed, experience, flexibility, engagement and enjoyment, making short-term decisions, iii. after the trip (reflective phase)—recollecting memories, sharing experiences, evaluating (making recommendations and suggestions) (Shen et al., 2020).
The stage of knowledge acquisition includes the trail of data left by the tourist during the planning, realization and post-trip phases, whether through evaluations or reports of experiences, or even organically throughout the entire journey experienced by the tourist. In this process of acquisition and use of data is where the mechanisms of knowledge governance could already work (Bocquet & Mothe, 2010; Moresi et al., 2020; Pinho et al., 2019; Wang et al., 2009; Gold, Malhotra, & Segars, 2001; Heisig, 2009; Chen & Mohamed, 2008).
Therefore, through the identification of the knowledge management processes used and the governance structures identified, it can be seen how the governance structures are constructed from the Knowledge Generation and Application Layer. Important the variables, such as economic, social, environmental indicators and other are considered in Data Input.
4.2 Knowledge Generation and Application Layer
The format that is envisaged for the TIS is the hybrid one (Clifton et al., 2010; Butler, 2020), as it comprises both network and market structures (Foss et al., 2010; Wang & Li, 2013; Amore & Hall, 2016), through horizontal relationships and mechanisms already presented and intended for this purpose.
The first ones play a market-oriented role with horizontal relationships and strategic and competitive permanence of the destination, which requires good dialogue and communication between stakeholders (Erkuş-Öztürk, 2011).
These centers would be organized into multidisciplinary working groups, considered as learning communities in the form of thematic cells (Hoetker & Mellewigt, 2009; Gerritsen et al., 2013).
Their organization would be by thematic chambers of interest of the various segments, regarding issues relevant to all, such as training, infrastructure, economy, investments, and others that are identified as necessary to be monitored. Thus, in the face of this organization, the application of knowledge is directed to the structure from the moment the governance mechanisms already presented are involved.
4.3 Knowledge Application Layer
The third layer, Knowledge Application, is where knowledge governance would actually take place. In this layer, all the knowledge generated through the TIS is delivered to the Destination Management Organizations (DMOs) as a subsidy for decision-making and competitiveness of the tourist destination.
This environment involves several spheres, so bringing to it the notion of private/public governance would also be a premise that, if it is managed like an organization, that could have a positive effect, through routines, rules, and administrative relationships among stakeholders.
As a preliminary conceptual framework of TIS based on GovC is represented in the Fig. 1.
The layered structure is supported by Fuchs et al. (2013), Garbani-Nerini et al. (2022), and Gretzel et al. (2015), who confirm the need to separate and identify these layers within an information system structure aimed at intelligence and destinations that want to work on knowledge. The proposed framework covered knowledge management processes to generate knowledge from the tourist’s journey. The governance mechanisms present themselves as a differentiated support to the TIS, aiming at its sustainability and competitiveness by part of destiny. The TIS structure indicates the various relationships and application formats for use of knowledge by the tourist trade.
5 Final Considerations
The TIS is the conceptual artifact to be obtained as a result of the implementation of Knowledge Governance. In turn, the KG will guide it through its structures and mechanisms necessary for the understanding of the tourist journey and the sustainability of the system, making the TIS a tool to support decision-making.
On the other hand, Tourism Governance brings its contribution in the management arrangement existing in the sector and in the understanding of the knowledge that can be generated for the elaboration of programs and public policies for tourism.
Therefore, the three constructs studied in this article were Tourism Intelligence System, Tourism Governance, and Knowledge Governance, and are aligned in an interdisciplinary way, since they come from different areas of knowledge: Technology, Tourism, and Knowledge Management. The search for publications on the subject showed the incipient relationship among these three constructs in the literature, verified in the methodology.
The proposed artifact can be considered not only a structure, but a possible “knowledge product”, being the preliminary result of steps 1 to 4 proposed in the methodology. From June to October 2023, it will undergo a structural verification by experts in the tourism sector and information technology of the destinations of the Latin American Smart Tourist Destinations Network (steps 5 and 6).
Notes
- 1.
Brazilian National Coordination for the Improvement of Higher Education Personnel.
References
Amore, A., & Hall, C. M. (2016). From governance to meta-governance in tourism? Re-incorporating politics, interests and values in the analysis of tourism governance. Tourism Recreation Research, 41(2), 109–122. https://doi.org/10.1080/02508281.2016.1151162
Bocquet, R., & Mothe, C. (2010). Knowledge governance within clusters: The case of small firms. Knowledge Management Research & Practice, 8(3), 229–239. https://doi.org/10.1057/kmrp.2010.14.
Botelho, L. L. R. De Almeida Cunha, C. C., & Macedo, M. (2011). O método da revisão integrativa nos estudos organizacionais. Gestão e sociedade, 5(11), 121–136. http://www.spell.org.br/documentos/ver/10515/o-metodo-da-revisao-integrativa-nos-estudos-organizacionais/i/pt-br.
Butler, R. W. (2020). Tourism carrying capacity research: A perspective article. Tourism Review, 75(1), 207–211. https://doi.org/10.1108/TR-05-2019-0194.
Chen, L., & Mohamed, S. (2008). Impact of the internal business environment on knowledge management within construction organizations. Construction Innovation, 8(1), 61–81. https://doi.org/10.1108/14714170810846521.
Clifton, N., et al. (2010). Network structure, knowledge governance, and firm performance: Evidence from innovation networks and SMEs in the UK. Growth and Change, 41(3), 337–373. https://doi.org/10.1111/j.1468-2257.2010.00529.x.
Crescencio, M. (2022). Modelo de uma rede colaborativa suportada por plataforma digital no domínio do turismo em patrimônio mundial cultural e natural. Tese (Programa de Pós-Graduação em Engenharia e Gestão do Conhecimento). UFSC: Florianópolis.
De Sá Freire, P., et al. (2017). Governança do Conhecimento (GovC): O estado da arte sobre o termo. Biblios, 69, 21–40. https://doi.org/10.5195/BIBLIOS.2017.469.
Erkuş-Öztürk, H. (2011). Modes of tourism governance: A comparison of Amsterdam and Antalya. Anatolia, 22(3), 307–325. https://doi.org/10.1080/13032917.2011.614354.
Foss, N. J. (2007). The emerging knowledge governance approach: Challenges and characteristics. Organization, 14(1), 29–52. https://doi.org/10.1177/1350508407071.
Foss, N. J., Mahoney, J. T., & De Pablos, P. O. (2010). Knowledge governance: Contributions and unresolved issues. International Journal of Strategic Change Management, 2(4), 263–268. https://doi.org/10.1504/IJSCM.2010.035846.
Fuchs, M.,Abadzhiev, A., Svensson, B., Höpken, W. & Lexhagen, M. (2013). A knowledge destination framework for tourism sustainability. TOURISM - An interdisciplinary journal. 61. 121–148. (2013). A knowledge destination framework for tourism sustainability: A business intelligence application from Sweden. Tourism: An International Interdisciplinary Journal, 61(2), 121–148. https://hrcak.srce.hr/file/157542.
Garbani-Nerini, E. (2022). From smart destinations to personalized communication. Travel and Tourism Reserach Association: Advancing Tourism Research Globally. TTRA International Conference, Victoria, British Columbia, June 14–16.
Gerritsen, A. L., Stuiver, M., & Termeer, C. J. (2013). Knowledge governance: An exploration of principles, impact, and barriers. Science and Public Policy, 40(5), 604–615. https://doi.org/10.1093/scipol/sct012.
Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal Management Information Systems, 18(1), 185–214. https://doi.org/10.1080/07421222.2001.11045669.
Gregersen, E. (2018). 5 components of information systems. Encyclopedia Britannica, 19 Mar. 2018, Disponível em: https://www.britannica.com/list/5-components-of-information-systems.
Gretzel, U., Koo, C., Sigala, M. & Xiang, Z. (2015). Special issue on smart tourism: Convergence of information technologies, experiences, and theories. Electronic Markets, 25(3), 175–177. https://doi.org/10.1007/s12525-015-0194-x.
Hall, C. M. (2011). Policy learning and policy failure in sustainable tourism governance: From first- and second-order to third-order change? Journal of Sustainable Tourism, 19(4), 649–671. https://doi.org/10.1080/09669582.2011.555555.
Heisig, P. (2009). Harmonisation of knowledge management—comparing 160 KM Frameworks around the globe. Journal of Knowlegde Management, 13(4), 4–31. https://doi.org/10.1108/13673270910971798.
Hoetker, G., & Mellewigt, T. (2009). Choice and performance of governance mechanisms: Matching alliance governance to asset type. Strategic Management Journal, 30(10), 1025–1044. https://doi.org/10.1002/smj.775.
Bono i Gispert, O. & Clavé, S. A. (2020). Dimensions and models of tourism governance in a tourism system: The experience of Catalonia. Journal of Destination Marketing & Management, 17. https://doi.org/10.1016/j.jdmm.2020.100465.
Moresi, E., Pinho, I., Pinho, C. & Costa, A. (2020). Mapping knowledge governance. In: ECRM 2020 20th european conference on research methodology for business and management studies: ECRM 2020. Academic Conferences and publishing limited. https://www.academic-conferences.org/conferences/ecrm/.
OECD. (2012). Tourism governance in OECD countries, in OECD tourism trends and policies 2012. OECD Publishing, Paris. https://doi.org/10.1787/tour-2012-3-en.
Otowicz, M. H., Lacerda, L. L. L., Emmendoerfer, L., & Biz, A. A. (2022). Tourism, knowledge management and its processes: An integrative literature review. Revista Brasileira de Pesquisa em Turismo, São Paulo, 16, e-2368. https://doi.org/10.7784/rbtur.v16.2368
O’BRIEN, J. A. (2020). Sistema de Informação e as decisões gerenciais na era digital. São Paulo: Saraiva.
Peffers, K., Tuuananen, T., Rothenberger, M. A. & Chatterjee, S. (2007). A design science research methodology for information systems research. Journal of management information systems, 24(3), 45–77. https://doi.org/10.2753/MIS0742-1222240302.
Pinho, I., Pinho, C. & Costa, A. P. (2019). Knowledge governance: building a conceptual framework. Fronteiras: Journal of Social, Technological and Environmental Science, 8(1), 72–92. https://doi.org/10.21664/2238-8869.2019v8i1.p72-92.
Shen, S., Sotiriadis, M., & Zhang, Y. (2020). The influence of smart technologies on customer journey in tourist attractions within the smart tourism management framework. Sustainability, 12(10), 4157. https://doi.org/10.3390/su12104157.
Soualah-Alila, F., et al. (2016). DataTourism: Designing an architecture to process tourism data. Information and communication technologies in tourism 2016 (pp. 751–763). Springer.
Trentin, F. (2017). Turismo e governança: Abordagem teórica. Universidade de Caxias do Sul.
Wang, H. C., He, J. & Mahoney, J. T. (2009). Firm‐specific knowledge resources and competitive advantage: the roles of economic‐and relationship‐based employee governance mechanisms. Strategic Management Journal, 30(12), 1265–1285. https://www.jstor.org/stable/27735491.
Wang, J., & Li, T. (2013). Review on tourist destination governance in foreign countries. Tourism Tribune, 28(6), 15–25. https://www.cabidigitallibrary.org/doi/full/10.5555/20133409438.
Ysa, T., Colom, J., Albareda, A., Ramon , A., Carrión, M. & Segura, L. (2014). Governance of addictions. European public policies. Oxford: Oxford University Press. ISBN: 9780198703303.
Acknowledgements
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior—CAPES/PROEX 489/2019.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Open Access This chapter is licensed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.
The images or other third party material in this chapter are included in the chapter's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the chapter's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
Copyright information
© 2024 The Author(s)
About this paper
Cite this paper
Emmendoerfer, L., Biz, A.A., de Sá Ferreira, P. (2024). Framework for a Tourism Intelligence System Based on Knowledge Governance: A Conceptual Model. In: Guevara Plaza, A.J., Cerezo Medina, A., Navarro Jurado, E. (eds) Tourism and ICTs: Advances in Data Science, Artificial Intelligence and Sustainability. TURITEC 2023. Springer Proceedings in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-031-52607-7_21
Download citation
DOI: https://doi.org/10.1007/978-3-031-52607-7_21
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-52606-0
Online ISBN: 978-3-031-52607-7
eBook Packages: Business and ManagementBusiness and Management (R0)