organizational factors driving technology non-adoption in australian tour operators

ENTER 2014 Research Track Slide Number 1

Organizational Factors Driving Technology Non-Adoption in

Australian Tour OperatorsUlrike Gretzel & Heather Kennedy-Eden

Institute for Innovation in Business and Social ResearchUniversity of Wollongong, Australia

&Nina Mistilis

Australian School of BusinessUNSW Australia

http://www.ifitt.org/


Agenda

• Introduction– Problem

– Previous research

• Method

• Evaluation results

• ConclusionThe research was developed from a commissioned report Tourism Operators' Digital

Uptake Benchmark Survey 2013 Research Report

http://tra.gov.au/publications/publications-list-693.html

http://tra.gov.au/publications/publications-list-693.html


Introduction

Problem:

– New ICTs allow tourism businesses to communicate globally

(Buhalis & Law, 2008);

– However, some still maintain traditional business practices instead

of adopting new ICTs (Gretzel & Fesenmaier, 2001)

– The concept innovation defectiveness is a structural problem in

tourism (Hjalager, 2002)

– Need to explore adoption/non adoption types and structural

(organisational) influences


Previous Research– Little known re ICT non-adoption in tourism organizations

– technology adoption & innovation research mostly based on Rogers’

(1995) Diffusion of Innovation theory

– But incomplete as:

1. Technology Adoption and Non-Adoption

• Does not inform why orgs choose NOT to adopt

• All adoption treated as equal

• Looks at one innovation – ignores potential ‘leapfrogging’ to advanced technology

(Hobday, 1995; Scaglione, Ismail, Trabichet, & Murphy, 2010)

• Ignores technology lock-in or stalling - delay for better cost or as too difficult

(Greenstein, 1997)

• Ignores using services of third party adopters


Previous Research Contd2. Organizational Factors Influencing Adoption/Non-Adoption

• technological, organizational, environmental contexts Zhu et al(2002)

• financial impacts and other factors (Nair, 1997).

• size of business (Gretzel et al, 2000) - but eg social media are affordable

• ownership structure – eg adoption decisions taken at head office

• tourism sectors exhibit different technology adoption patterns (Fisher & Beatson, 2002).

• digital divide between rural and urban areas (Gretzel et al 2009)


Method – Data Collection– Empirical data collected in May-June, 2013 survey of tourism

operators in Australia

– five selected industry sectors (Accommodation, Dining, Attractions,

Tours, Hire/Rentals)

– Computer Assisted Telephone Interviewing (CATI) and an online

survey of randomly selected Australian Tourism Data Warehouse

members.

– 1200 respondents (CATI survey) and 972 responses (online survey)


Method – Data Analysis

Respondents classified into categories depending on their

technology adoption:

1. Non-adopters – no webpage or social media presence,

2. Proxy-adopters - no webpage or social media but information

listed through a third party website;

3. Adopters - webpage and a social media presence;

4. Leapfroggers –no webpage but social media presence; and

5. Stallers - webpage but no social media presence.


Method - IVsFive organizational factors identified in relation to technology

adoption or non-adoption:

(1) Size (2) location of organization, (3) type of business (stand

alone, franchise, part of group/chain, govt, not-for-profit),

(4) industry sector - accom44%; din29%; TA/tours12%; attr11%;

hire/rental4%

& as focus was on technology for online distribution:

(5) took bookings/reservations

X-tabs & chi-square tests used to investigate if adoption/non-

adoption groups differed across organizational variables.


Descriptive results– Distribution among adopter categories:

1. adopter (61.9%)

2. leapfrogger (6.2%)

3. staller (20.8%)

4. proxy-adopter (4.2%)

5. non-adopter (6.5%)

-significant differences in pattern of adoption across industry sectors

eg accommodation v dining


Influence of Organizational Factors

Table 1. Organizational Factors by Adopter/Non-Adopter Group

Non-

adopter Proxy-Adopter Staller Leap-frogger Adopter Chi Square

Core business Industry sector

Accommodation 17.6 47.3 61.3 21.6 43.0 273.8** Dining 64.1 33.0 16.0 67.2 25.6 Attractions 4.2 13.2 7.8 7.5 13.0 Tours 7.7 4.4 10.7 3.0 14.2 Hire/Rentals 6.3 2.2 4.2 0.7 4.2

Takes bookings 70.2 84.6 94.9 83.6 95.2 140.4** Organizational Structure Organization Type

Stand-alone 89.4 77.8 79.6 81.5 79.4 24.4* Franchise 2.8 2.2 2.0 3.7 3.6 Chain/Group 5.6 10.0 10.4 8.1 13.4 Other 2.1 10.0 8.0 6.7 8.0

Size of Organization < 5 people 56.8 61.1 59.3 43.3 44.2 96.9** 5 to 9 27.3 15.6 18.0 23.9 15.4 10 to 19 10.1 14.4 11.9 17.9 16.6 20 to 199 5.0 5.6 7.9 10.4 15.6 200 or more 0.7 3.3 2.9 4.5 8.2

Organizational Environment Urban 37.4 25.3 32.4 26.1 39.2 21.3** Semi-urban 51.8 58.2 54.7 55.2 48.5 Rural 10.8 16.5 12.9 18.7 12.3

Note: * = significant at the .05 level; ** = significant at .01 level


Results I– Non-adopters more likely dining

– Proxy-adopters more likely accommodation

– Stallers more likely accommodation businesses

– Leapfroggers more likely dining establishments

– Adopters more likely attractions and tour companies

– Adopters, Stallers (each 95%) followed by Leapfroggers, Proxy-

Adopters (each 85%) are more likely to take bookings:

ie reservations online fosters Web 1.0 not Web 2.0

uptake.


Results II– Non-adopters more likely stand-alone

– Adopters are biggest organisations

– Adopters & Non-adopters more likely urban or semi urban,

indicating similar geographic distribution

ie urban environment per se does not guarantee digital

sophistication

- Slightly higher % of leapfroggers are rural

ie Web 2.0 may overcome lack of infrastructure halting Web 1.0

adoption in rural areas


Future Research

Need greater understanding:• leapfrogging & its effects on productivity• Industry sector effects associated with non

adoption patterns• A sophisticated analysis of additional

organisation factors influencing non adoption patterns beyond this initial step


ConclusionsFindings indicate:

– five adoption/non-adoption groups

– certain types of organizations are more likely to fall within a

particular adoption/non-adoption type

– government policies must consider various types of innovation &

deliberate non-adoption

– policy to overcome innovation deficiencies must target sectors not

overall industry


Organizational Factors Driving Technology Non-Adoption in Australian Tour Operators

Ulrike Gretzel Heather Kennedy-Eden & Nina Mistilis Questions?

http://www.ifitt.org/