The impact of big data on firm performance in hotel industry

被引：90

作者：

Yadegaridehkordi, Elaheh ^{[1
]}

Nilashi, Mehrbakhsh ^{[2
,3
]}

Shuib, Liyana ^{[1
]}

Nasir, Mohd Hairul Nizam Bin Md ^{[4
]}

Asadi, Shahla ^{[5
]}

Samad, Sarminah ^{[6
]}

Awang, Nor Fatimah ^{[7
]}

机构：

[1] Univ Malaya, Fac Comp Sci & Informat Technol, Dept Informat Syst, Kuala Lumpur 50603, Malaysia

[2] Ton Duc Thang Univ, Dept Management Sci & Technol Dev, Ho Chi Minh City, Vietnam

[3] Ton Duc Thang Univ, Fac Informat Technol, Ho Chi Minh City, Vietnam

[4] Univ Malaya, Fac Comp Sci & Informat Technol, Dept Software Engn, Kuala Lumpur 50603, Malaysia

[5] Univ Putra Malaysia, Fac Comp Sci & Informat Technol, Dept Software Engn & Informat Syst, Serdang 43400, Selangor, Malaysia

[6] Princess Nourah Bint Abdulrahman Univ, Collage Business & Adm, Dept Business Adm, Riyadh, Saudi Arabia

[7] Natl Def Univ Malaysia, Fac Def Sci & Technol, Kuala Lumpur, Malaysia

来源：

ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS | 2020年 / 40卷

关键词：

Firm performance; Big data; Hotel industry; Fuzzy logic; Structural equation modelling; ORGANIZATION-ENVIRONMENT FRAMEWORK; HOSPITAL INFORMATION-SYSTEM; TASK-TECHNOLOGY FIT; E-BUSINESS; INNOVATION ADOPTION; DATA ANALYTICS; DETERMINANTS; SMES; INTENTION; CAPABILITIES;

D O I：

10.1016/j.elerap.2019.100921

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

Big data has increasingly appeared as a frontier of opportunity in enhancing firm performance. However, it still is in early stages of introduction and many enterprises are still un-decisive in its adoption. The aim of this study is to propose a theoretical model based on integration of Human-Organization-Technology fit and TechnologyOrganization-Environment frameworks to identify the key factors affecting big data adoption and its consequent impact on the firm performance. The significant factors are gained from the literature and the research model is developed. Data was collected from top managers and/or owners of SMEs hotels in Malaysia using online survey questionnaire. Structural Equation Modelling (SEM) is used to assess the developed model and Adaptive NeuroFuzzy Inference Systems (ANFIS) technique is used to prioritize adoption factors based on their importance levels. The results showed that relative advantage, management support, IT expertise, and external pressure are the most important factors in the technological, organizational, human, and environmental dimensions. The results further revealed that technology is the most important influential dimension. The outcomes of this study can assist the policy makers, businesses and governments to make well-informed decisions in adopting big data.

引用

页数：20