Comparing efficiency in all-inclusive and bed and breakfast hotel businesses: a multi-period data envelopment analysis in Turkey

IF 4.2 Q2 BUSINESS
Y. Günaydin, A. Correia, M. Kozak
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引用次数: 3

Abstract

PurposeThis paper aims to understand the most efficient hotel system and why efficiency varies across years and between the two differing types of hotel businesses in Turkey.Design/methodology/approachA data envelopment analysis (DEA) analysis was used to characterise the efficiency of all-inclusive (AI) and bed and breakfast (B&B) hotel businesses with one output (total revenue) and three inputs (labour, food and capital costs). The Malmquist approach is then used to discern changes in total efficiency (TTE) and intertemporal shifts in the efficiency frontier (technological change (Tch)).FindingsThe results reveal that the AI hotel operates at 100% efficiency in the summer and year-round. The B&B hotel business operates at 89.6% with variable constant returns to scale during the summer and with 100% efficiency. The results of the Malmquist approach indicate that the total factor productivity grew in the years 2015, 2016, 2018 and 2019, while the other years were marked by inefficiency. Such increases were due to technical efficiency change (TEch) and Tch, which means that managerial and allocative efficiency (AE) were barely achieved. Slight differences were noted in the two time periods (all year and summer), suggesting that the scale of hotel businesses is prepared to operate all year round, and this calls for strategies to mitigate seasonality.Research limitations/implicationsAs to avenues for future research, the limitations of this study are threefold. First, the hotel businesses are not parallel in terms of the duration of their service offerings. Future research may consider including an AI hotel business that is in operation for the whole year. Second, businesses in Turkey are sceptical about sharing their data as it is considered confidential. However, to better generalise the results and encourage hoteliers to consider the positive outcomes of such analysis, the number of observations could be increased by considering more hotel businesses in both categories. Third, a mixture of data representing businesses operating in various countries may reflect if the efficiency scores vary internationally.Practical implicationsOverall, AI hotel businesses are more attractive but less efficient than B&B. Furthermore, the external crisis impacts the efficiency of hotel businesses meaning that hotel managers could keep on exploring AI, perhaps educating their hosts not to waste or not offer huge quantities. Hotel managers may also need to enlarge their seasonal activities to ensure more efficiency.Social implicationsDespite the intentions of AI hotel businesses to increase their profitability with a lower level of service quality, this study shows that the AI hotel business is very attractive but not so efficient due to the higher propensity of guests to consume food and beverages in excess that compromises the definition of efficiency as zero waste. AI is very attractive for family groups or those seeking the pleasure of relaxation at seaside resorts and is also very popular in Turkey. On the other hand, the B&B hotel business is more efficient but less attractive.Originality/valueThe contributions of this paper are threefold. First, the authors analysed the efficiency and inefficiency of hotel businesses within nine years of operations. During this period, Turkey experienced first a tourism boom (2011–2014) followed by stagnation and subsequently a sharp decline due to political instability resulting in an (in)direct impact on tourism (2015–2019). Second, the authors compared the efficiency and inefficiency of AI and B&B hotel businesses. Third, the authors examined the effects of hotel management factors to ensure efficiency.
比较全包和住宿加早餐酒店业务的效率:土耳其的多期数据包络分析
目的本文旨在了解土耳其最高效的酒店系统,以及为什么效率在不同年份以及两种不同类型的酒店业务之间存在差异。设计/方法/方法使用数据包络分析(DEA)分析来描述一项产出(总收入)和三项投入的全包(AI)和住宿加早餐(B&B)酒店业务的效率(劳动力、食品和资本成本)。然后使用Malmquist方法来识别总效率(TTE)的变化和效率前沿的跨期变化(技术变化(Tch))。结果表明,人工智能酒店在夏季和全年都以100%的效率运营。民宿酒店业务的运营率为89.6%,夏季的规模回报率可变,效率为100%。Malmquist方法的结果表明,全要素生产率在2015年、2016年、2018年和2019年增长,而其他年份则表现为低效率。这种增长是由于技术效率变化(TEch)和Tch,这意味着管理和配置效率(AE)几乎没有实现。在这两个时间段(全年和夏季)发现了轻微的差异,这表明酒店业务的规模已准备好全年运营,这需要采取策略来缓解季节性。研究局限性/含义关于未来研究的途径,本研究的局限性有三方面。首先,酒店业务在提供服务的持续时间方面并不平行。未来的研究可能会考虑将全年运营的人工智能酒店业务纳入其中。其次,土耳其的企业对共享他们的数据持怀疑态度,因为这些数据被视为机密。然而,为了更好地概括结果并鼓励酒店经营者考虑此类分析的积极结果,可以通过考虑这两类酒店中的更多酒店业务来增加观察次数。第三,代表在不同国家经营的企业的混合数据可能反映出效率得分是否在国际上有所不同。实际含义总体而言,人工智能酒店业务比民宿更有吸引力,但效率较低。此外,外部危机影响了酒店业务的效率,这意味着酒店经理可以继续探索人工智能,也许可以教育他们的主人不要浪费或不要提供大量服务。酒店经理可能还需要扩大他们的季节性活动,以确保更高的效率。社会影响尽管人工智能酒店企业的意图是通过降低服务质量来提高盈利能力,但这项研究表明,人工智能酒店业务非常有吸引力,但效率并不高,因为客人更倾向于过度消费食品和饮料,这损害了零浪费效率的定义。人工智能对家庭团体或在海滨度假胜地寻求放松乐趣的人非常有吸引力,在土耳其也很受欢迎。另一方面,民宿酒店业务效率更高,但吸引力较小。这篇论文的贡献有三个方面。首先,作者分析了酒店业务在运营九年内的效率和低效率。在此期间,土耳其首先经历了旅游业的繁荣(2011-2014年),随后出现了停滞,随后由于政治不稳定而急剧下降,对旅游业产生了直接影响(2015-2019年)。其次,作者比较了人工智能和民宿酒店业务的效率和低效率。第三,考察了酒店管理因素对效率的影响。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
6.90
自引率
0.00%
发文量
21
审稿时长
24 weeks
期刊介绍: European Journal of Management and Business Economics is interested in the publication and diffusion of articles of rigorous theoretical, methodological or empirical research associated with the areas of business economics, including strategy, finance, management, marketing, organisation, human resources, operations, and corporate governance, and tourism. The journal aims to attract original knowledge based on academic rigour and of relevance for academics, researchers, professionals, and/or public decision-makers.
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