Author Bios (50 Words for each Author)

Michelle Novotny is currently a Master of Science and Management student at the Ted Rogers School of Management, Ryerson University, Canada. Her research interests are in sustainable tourism development.

Dr. Rachel Dodds is a Professor at the Ted Rogers School of Hospitality and Tourism Management, Ryerson University, Canada. With over 25 years of practical and academic experience, her work focuses on practical management strategies for the sustainable development of tourism.

Dr. Philip Walsh is a Professor at the Ted Rogers School of Entrepreneurship and Strategy, Ryerson University, Canada. With over 38 years of industry and academic experience, his teaching and research focuses on strategy, sustainability, and innovation.

Abstract (150 Words)

DMOs have increasingly been called upon to make “smart”, data-driven, destination management decisions; however, a great portion of DMOs continue to struggle to obtain adequate data and preform the required analyses. One proposed solution is a destination management information system (DMIS) - a decision support system to aid DMOs in data-driven management decisions. However, the existing literature on DMIS applications comprises primarily of single case studies. Therefore, through a three-phase mixed-methods approach, the present study set out to develop and test a scalable DMIS prototype across two pilot destinations within Canada in its capacity to support smart destination management decisions. Findings indicated that the DMIS was scalable within Canada and supported DMOs in making smart destination management decisions but was ultimately limited by the quality of available tourism data inputs. Opportunities for future knowledge generation and knowledge application in the tourism industry are discussed along with areas for future research.

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Developing a Scalable Data-Driven Decision-Making Tool for Smart Destination Management

DMOs have increasingly been called upon to make “smart”, data-driven, destination management decisions; however, a great portion of DMOs continue to struggle to obtain adequate data and preform the required analyses. One proposed solution is a destination management information system (DMIS) - a decision support system to aid DMOs in data-driven management decisions. However, the existing literature on DMIS applications comprises primarily of single case studies. Therefore, through a three-phase mixed-methods approach, the present study set out to develop and test a scalable DMIS prototype across two pilot destinations within Canada in its capacity to support smart destination management decisions. Findings indicated that the DMIS was scalable within Canada and supported DMOs in making smart destination management decisions but was ultimately limited by the quality of available tourism data inputs. Opportunities for future knowledge generation and knowledge application in the tourism industry are discussed along with areas for future research.