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Key Factors in the Process of Acceptance and Implementation of Artificial Intelligence in the Hotel Sector
Abstract
Artificial intelligence is one of the most innovative and trending technologies in the hotel sector. It is transforming the hotel sector into a novel environment in business-client relationships. For this reason, this study seeks to find, through a literary review and a causal study carried out by experts in technologies and hotels, using the methodology of fuzzy cognitive maps, what the determining factors in the decision of hotels to accept and implement artificial intelligence in their hotels and in their services are. The list obtained is made up of the following factors (in order of relevance in this decision): top management support, perceived reliability of the technology, security, relative advantage, support from information systems providers, technological organizational readiness, government pressure or incentives, compatibility, business partner pressure, customer pressure, complexity, pressure from competitors, perceived cost, characteristics of the leader or manager, and size of the company.
... The extant literature on AI has not specifically investigated the critical success or failure factors AI implementation. The majority of the studies examined the impact of the implementation of AI systems on the organizations in different industries (e.g., Gill et al., 2019;Infante-Moro et al., 2021;Williams et al., 2018). The rest of this section presents studies that indirectly mentioned the barriers to AI systems. ...
... In AI literature, researchers argued and found top management support to be a critical factor impacting AI implementation. For instance, using the methodology of fuzzy cognitive maps, Infante-Moro et al. (2021) found top management support to be on the top of the list of the factors impacting the decision to accept and implement AI in the hotels sector. Top management should be involved in assigning the necessary resources during the whole period of the project and a little while after because there are always update and upgrades in the technology industry. ...
AI systems offer organizations great benefits causing decision-makers to invest more in these systems. The advantages of AI cannot be achieved without successful implementation. Thus, it is crucial to recognize the factors impacting the successful implementation of AI. It is also important to assess and rank these factors by their importance to assist decision-makers in implementing these systems and increasing the success rate. Due to its importance, scholars called for studies to expand our knowledge in this critical area. This paper identifies, extracts, and assesses the most critical factors that influence the implementation of AI systems. This study identifies nineteen factors and categorizes them into four categories: organization, technology, process, and environment. The analytical hierarchy process is used to evaluate the factors and the categories. The analysis offers two types of results, at the category level and the level of the factors. The results indicate that technology is the most significant of the four categories. The results also suggest that ethics is the most crucial factor among all nineteen factors. The order of all factors and discussions of the implications of the findings for practice and research are presented in the paper.
... The extant literature on AI has not specifically investigated the critical success or failure factors AI implementation. The majority of the studies examined the impact of the implementation of AI systems on the organizations in different industries (e.g., Gill et al., 2019;Infante-Moro et al., 2021;Williams et al., 2018). The rest of this section presents studies that indirectly mentioned the barriers to AI systems. ...
... In AI literature, researchers argued and found top management support to be a critical factor impacting AI implementation. For instance, using the methodology of fuzzy cognitive maps, Infante-Moro et al. (2021) found top management support to be on the top of the list of the factors impacting the decision to accept and implement AI in the hotels sector. Top management should be involved in assigning the necessary resources during the whole period of the project and a little while after because there are always update and upgrades in the technology industry. ...
This study aims to fill a gap in the literature by identifying and extracting critical success factors that impact the success of AI implementation. The factors are then categorized and presented in a process model that demonstrates the sequence of the factors and the interrelationships among them. The model is composed of three stages: pre-implementation, implementation, and post-implementation. The implementation is composed of three categories organization, process, and technology. Each of these categories contains several critical factors. The model presented helps both researchers and practitioners. Details, discussion, and future research opportunities are discussed in the paper.
... In fact, the hospitality business processes integrate easily with IT applications before the pandemic impacts. IT is and continues to be a major force affecting changes in the service industry, reshaping the dynamics of competition, and customers' and employees' interactions (Infante-Moro, Infante-Moro& Gallardo-Pérez, 2021). For these reasons, IT and service industry have become great allies, which could be explained because of many of the IT functions which have been aimed at service business solutions. ...
Information Technology (IT) has dramatically changed the way in which businesses, organizations, governments, and individuals interact since COVID19 pandemic was declared in 2020. To produce services in the current hospitality industry is complex and sometimes challenging. In order to face the limitations of the hospitality market producer adopted and adapted new information technologies to remain competitive.
... The number of interviewees in a study that uses a fuzzy cognitive map is fixed according to the number of new influencing factors per interview [79,80]; that is, the number of interviewees is adequate from the moment the interviewees stop providing new factors (to those provided by previous interviewees) to the system. This means that there was no predetermined number of interviewees, and that studies could have varying sample sizes: 45 [81], 41 [82], 30 [83,84], 29 [81], 8 [85,86] or 7 [74] and up to 4 experts [87]. In this study, the number of interviewees was set at 40 to give the results the greatest possible significance despite the fact that none added new factors, and this number could have been lower. ...
Many of the tools used for virtual teaching during the pandemic had not been used previously, but they could continue to be used when traditional teaching returns. For this reason, this study focused on locating the key motivational factors for the possible continuation of the use of one of these tools, videoconferencing, to carry out tutorials in Spanish universities as a complement to face-to-face tutorials. For this, a literary review was conducted to obtain a list of motivational factors that may influence teachers to continuing using it, and a causal study was performed with university professors (through fuzzy cognitive maps) to identify the causal relationships among these factors and classify them by their relevance in making a decision. The most influential factors are intention, attitude and perceived compatibility with how tutorials are given, and the negative factors include quality management and trust.
In the framework of the pandemic caused by CoVId-19, education worldwide, as a preventive measure, went from face-to-face to virtual. The untimely manner of this change, and without prior preparation, brought difficulties and also some advantages to doctoral students. This forced some authors to create a documentary measurement instrument called "doctoral students’ virtual learning perception in the CoVId-19 framework" with four dimensions and 30 items on a Likert-type scale. The objective of this work is to present from the quantitative approach the internal and external validity of the mentioned instrument. The results show a Cronbach's alpha coefficient, initial and final, greater than 0.8 and a Pearson correlation coefficient different from zero. It is concluded that the analyzed instrument is not only sufficient and relevant, but also has validity because it is reliable and stable. © 2021 Red Universitaria de Campus Virtuales. All rights reserved.
Las titulaciones y los programas formativos deben estar acordes a las competencias que demanda el mercado, ya que encontrar empleo se ha vuelto un proceso complicado y competitivo, y esto aumenta las posibilidades de encontrarlo. Por este motivo, y por la importancia que han adquirido las competencias digitales en el sector turístico, desde el Máster de Turismo de la Universidad de Huelva se pretende hacer un análisis de las competencias digitales en su programa formativo, haciendo una comparativa entre el dominio de competencias que tienen sus estudiantes y el dominio de competencias que demanda el sector turístico. Este análisis se desarrolla a través de un cuestionario realizado a 21 estudiantes del último curso del máster y a 10 profesores del máster que pertenecen al ámbito empresarial del sector turístico en la provincia donde se imparte, y concluye que en líneas generales los estudiantes de esta titulación poseen las competencias digitales generales que demanda el sector y las competencias digitales necesarias para que el proceso de encontrar empleo sea lo más corto posible, lo que puede ayudar a que el máster mantenga su alto nivel de empleabilidad entre sus estudiantes.
CAMPUS VIRTUALES del Carpio Ramos, h. A.; del Carpio Ramos, P. A.; garcía-Peñalvo, f. J.; del Carpio hernández, S. R. b. (2021). Validez de instrumento: percepción del aprendizaje virtual durante la CoVId-19. Campus Virtuales, 10(2), 111-125. www.revistacampusvirtuales.es RESUMEn. En el marco de la pandemia originada por la CoVId-19 la educación a nivel mundial, como medida de prevención, pasó de la forma presencial a la virtual. La manera intempestiva de este cambio y sin preparación previa trajo dificultades y también algunas ventajas a los estudiantes de doctorado. Esto obligó a algunos investigadores a crear un instrumento de medición documental denominado "Percepción del aprendizaje virtual de doctorandos en el marco de la CoVId-19" de cuatro dimensiones y 30 ítems en escala del tipo Likert. El objetivo de este trabajo es presentar desde el enfoque cuantitativo la validez interna y externa del instrumento mencionado. Los resultados muestran un coeficiente Alfa de Cronbach, inicial y final, mayor a 0,8 y un coeficiente de correlación de Pearson diferente de cero. Se concluye que el instrumento analizado, no solo es suficiente y pertinente, sino que también, presenta validez porque es confiable y estable. AbSTRACT. In the framework of the pandemic caused by CoVId-19, education worldwide, as a preventive measure, went from face-to-face to virtual. The untimely manner of this change, and without prior preparation, brought difficulties and also some advantages to doctoral students. This forced some authors to create a documentary measurement instrument called "doctoral students' virtual learning perception in the CoVId-19 framework" with four dimensions and 30 items on a Likert-type scale. The objective of this work is to present from the quantitative approach the internal and external validity of the mentioned instrument. The results show a Cronbach's alpha coefficient, initial and final, greater than 0.8 and a Pearson correlation coefficient different from zero. It is concluded that the analyzed instrument is not only sufficient and relevant, but also has validity because it is reliable and stable. PALAbRAS CLAVE: Instrumento, Aprendizaje virtual, Percepción, doctorado, CoVId-19.
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