4.4 Article

Factors affecting energy-efficiency investment in the hotel industry: survey results from Spain

Journal

ENERGY EFFICIENCY
Volume 14, Issue 4, Pages -

Publisher

SPRINGER
DOI: 10.1007/s12053-021-09936-1

Keywords

Hotel industry; Energy-efficiency HVAC system; Barriers; Environmental attitudes; Energy efficiency investments

Funding

  1. EU [723741]
  2. Spanish State Research Agency through Maria de Maeztu Excellence Unit accreditation 2018-2022 [MDM-2017-0714]
  3. Basque Government BERC programme
  4. Government of Spain
  5. European Regional Development Fund [RTI2018-093692-B-I00, RTC2019007315-3, RED2018-102794-T]
  6. H2020 Societal Challenges Programme [723741] Funding Source: H2020 Societal Challenges Programme

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The study reveals that the evaluation of energy efficiency in HVAC system investment by hotel owners is influenced by various factors such as climate conditions, environmental concerns, hotel types, and other attributes of the HVAC system. Hotel industry may perceive energy efficiency as a quality indicator rather than just a cost-saving measure.
Increasing energy efficiency is a major way of saving energy and thus reducing energy expenses. However, adoption of energy efficiency is generally low, as demonstrated by the energy efficiency gap. To understand that gap, this paper analyses the factors that affect how the energy efficiency attribute is rated in investment in heating, ventilation and air conditioning (HVAC) systems in the hotel industry in Spain. A survey conducted on two hundred owners of hotels, hostels and holiday cottages (referred to jointly here for the sake of convenience as the hotel industry) shows that the value placed on energy efficiency is influenced not just by climate conditions, environmental concern and type of hotel but also by other attributes of the HVAC system such as brand reliability, price and performance. The hotel industry may also be identifying EE as a proxy for quality rather than savings. Designing the right energy-efficiency policy entails accounting for potential responses by agents, and this analysis helps identify those drivers to which they may or may not respond.

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