Internet Use by Hospitality SMEs in Alpine Destinations

Schegg, Roland; Scaglione, Miriam; Liebrich, Andreas; Murphy, Jamie

doi:10.1007/978-3-211-69566-1_43

Cited by 10 publications

(4 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…According to these authors, early adopters invested more in these technologies, made better and wider use of them such as quality websites and e-service, and seemed more successful in website traffic and online bookings. In line with prior diffusion research, there were significant positive relationships between hotel size, category and affiliation with IT performance (Schegg et al, 2007). (Marvel, 2004).…”

Section: Introductionsupporting

confidence: 68%

“…Schegg et al (2002) corresponds to the first of three stages -publishing sites; databases/forms; and personalization -of website evolution (Hanson, 2000). A recent study (Schegg et al, 2007) on a representative sample of 182 hospitality enterprises across six Austrian, German and Swiss alpine destinations showed evolving Internet adoption (Murphy et al, 2006 and references therein); website ages tended to reflect advanced website features and IT use. According to these authors, early adopters invested more in these technologies, made better and wider use of them such as quality websites and e-service, and seemed more successful in website traffic and online bookings.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Website adoption and sales performance in Valais’ hospitality industry

Scaglione¹,

Schegg²,

Murphy

2009

Technovation

Self Cite

View full text Add to dashboard Cite

Available Room or RevPAR. That is, the RevPAR of hotels was higher after adoption than before and hotels with no web presence showed a negative trend in revenues.Furthermore, revenue growth rates were stronger for hotels with their own website than for hotels with a web presence via regional portals. These patterns suggest that Internet technologies have a positive impact on hotel performance, perhaps via improved marketing and distribution.

show abstract

Section: Introductionsupporting

confidence: 68%

Section: Introductionmentioning

confidence: 99%

Website adoption and sales performance in Valais’ hospitality industry

Scaglione¹,

Schegg²,

Murphy

2009

Technovation

Self Cite

View full text Add to dashboard Cite

show abstract

“…Even while recognizing nowadays the rising importance of online distribution channels in tourism (Li et al , 2009), many (Swiss) hotels still do not fully exploit their own Web sites (Murphy et al , 2003; Schegg et al , 2007) as a tool for selling hotel rooms directly and gaining competitive advantage (Law and Jogaratnam, 2005). Instead, many small- and medium-sized enterprises (SMEs) in the hotel sector are challenged by the vast number of opportunities and the variety of alternative distribution systems (Toh et al , 2011).…”

Section: Introductionmentioning

confidence: 99%

Maximizing online bookings through a multi-channel-strategy

Beritelli

Schegg²

2016

IJCHM

Self Cite

View full text Add to dashboard Cite

Purpose Hotel managers are being challenged by the increasing multitude of distribution and sales channels. Online travel agencies (OTAs) in particular generate a great deal of uncertainty: Which are the best ones? Which ones offer the best conditions? How many channels are optimal for my hotel? How can I evaluate costs versus benefits? These and other questions concerning the optimal online distribution channel strategy have produced different reactions in practice. The aim of this paper is to challenge the need for an over-optimization of channel strategy by proposing that the consumer, at the end, deals with a network of information presented on one networked environment, including the Web. Hence, the network effect of the numerous online platforms is what drives consumer choice and, finally, bookings. Design/methodology/approach A series of multiple regressions with representative samples of hotels in Switzerland from the years 2009, 2010, 2011 and 2012 was performed to estimate the importance of the number of platforms against other independent variables. Additionally, further multiple regressions with samples from the years 2011 and 2012 using the most important platforms (first-tier channels) shows again that the number of platforms is more important. Findings The analyses show that the estimated number of online bookings by the respondents in the hotels is a result of the number of channels, not the type of channel. This is particularly true for non-categorized establishments and one- and two-star hotels. The analyses do not confirm the billboard effect, according to which particular platforms (first-tier channels) increase the probability of bookings. Thus, the survival strategy is to maximize share of shelf and to build on interdependencies and network effects. Research limitations/implications The study looks only at online bookings. Additional research into the connection between online and offline channels, particularly from the viewpoint of the consumer, will provide further insights. The study looks at the booking volume per channel, not the monetary sales volume or the profit. A study that quantifies not only the volume of bookings but also the total profit or the contribution to profit per channel could quantify the benefits of the multi-channel strategy. Originality/value The multiple online channel strategy seems to be the more effective approach to maximizing bookings online, regardless of the platforms chosen. Results of the study challenge the current opinion among practitioners that the multitude of distribution channels forces them to choose among single online channels and, therefore, drives the search for criteria to assess these channels or even to disregard them. The consistent results across 2009-2012 show that even in the turbulent phase of the advent of OTAs in the travel industry, hotels can adopt a winning strategy. Finally, the results suggest that the intermediation of online distribution of hotel beds has approached the condition of perfect competition, causing the OTA business model to be cannibalized.

show abstract

“…Rank effects include sector/supply chain characteristics (considering technology intensiveness of sectors, supply chain influence); the technology cluster making up a technology system (Rosenberg, 1982); organisational action, such as age of management and experience (Palvia and Palvia, 1999), gender of the managers (Igbaria et al, 1998), management approach to ICT, organisational structure and ICT adoption strategies, which relate to the drivers for ICT adoption (Singh and Kasavana, 2005), and business strategy (Hashim et al, 2006;Miles and Snow, 1978); and business endogenous characteristics, including size (Arvanitis and Stern, 2001;Schegg et al, 2007), business age (Arvanitis and Stern, 2001), rating category and corporate status (Schegg et al, 2003) and the technological ecology [including the geographical location, the technology substitution, which can occur within systems' components (Windrum and de Berranger, 2002)].…”

Section: Framework For Etourism Capabilitymentioning

confidence: 99%

A benchmarking framework for eTourism capability of destinations’ industries

Reino¹,

Frew

Mitsche

2014

Journal of Hospitality and Tourism Technology

View full text Add to dashboard Cite

Purpose – This paper aims to provide a framework for benchmarking the eTourism capability of a destination’s tourism industry, understanding the eTourism capability of a destination’s industry as the contribution that the information and communication technologies (ICT) uptake of that industry makes to its own performance. The impact of ICT in tourism has been suggested through extensive research. Previous work has urged the development of wide-angle studies to enable benchmarking of destinations and their industries. However, relevant research is limited. Macro-level studies in the area tend to focus on a single aspect of technology to evaluate adoption, are not sector-specific nor take into consideration the different levels of contribution that systems may bring to performance. Design/methodology/approach – A review of the literature on tourism, eTourism, benchmarking and technology adoption provided the baseline for developing this benchmarking tool. Findings – The literature supported the selection of key tourism industry sectors, i.e. accommodation establishments, visitor attractions and food and beverage; the most suitable methodology, i.e. intermediary performance measures; and the business characteristics that need being taken into consideration when assessing ICT adoption by tourism businesses, e.g. size, type of establishment and area of location. Research limitations/implications – The framework has not been tested yet. It is based on a review of the literature and needs to be validated through primary research. The framework was developed based on the context of Scotland. Further work should be done to adjust the framework to other destinations worldwide. Practical implications – The framework enables destinations to benchmark the eTourism capability of their industries. Originality/value – It provides a comprehensive framework for benchmarking tourism destinations’ industries, which takes into consideration elements of technology adoption, the characteristics of the tourism industry and the particularities of the different ICT elements.

show abstract

Internet Use by Hospitality SMEs in Alpine Destinations

Cited by 10 publications

References 22 publications

Website adoption and sales performance in Valais’ hospitality industry

Website adoption and sales performance in Valais’ hospitality industry

Maximizing online bookings through a multi-channel-strategy

A benchmarking framework for eTourism capability of destinations’ industries

Contact Info

Product

Resources

About