What is he best known for?
The fields of study he is best known for:
- Marketing
- Social psychology
- The Internet
The scientist’s investigation covers issues in Marketing, Advertising, Loyalty, Context and Structural equation modeling.
His Service quality, Customer satisfaction and Consumer behaviour study in the realm of Marketing interacts with subjects such as Destinations and Hospitality industry.
He works mostly in the field of Consumer behaviour, limiting it down to concerns involving Word of mouth and, occasionally, User-generated content.
His Advertising research is multidisciplinary, incorporating perspectives in Social media, Web design and Conversion marketing.
The various areas that Anil Bilgihan examines in his Loyalty study include Loyalty business model and Social psychology.
His Context study combines topics from a wide range of disciplines, such as Organizational commitment and The Internet.
His most cited work include:
- Understanding Satisfied and Dissatisfied Hotel Customers: Text Mining of Online Hotel Reviews (227 citations)
- Customer loyalty: a review and future directions with a special focus on the hospitality industry (218 citations)
- Gen Y customer loyalty in online shopping (171 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Marketing, Advertising, Hospitality industry, Hospitality and Context.
His work on Loyalty, Service and Service provider as part of his general Marketing study is frequently connected to Hospitality management studies and Information technology, thereby bridging the divide between different branches of science.
His Loyalty study incorporates themes from Big Five personality traits, Loyalty business model and Social psychology, Organizational commitment.
His Loyalty business model research includes themes of Customer satisfaction and Customer retention.
His research in the fields of Consumer behaviour overlaps with other disciplines such as Structural equation modeling.
The study incorporates disciplines such as Brand image, Applied psychology and Service recovery in addition to Context.
He most often published in these fields:
- Marketing (55.96%)
- Advertising (35.78%)
- Hospitality industry (21.10%)
What were the highlights of his more recent work (between 2019-2021)?
- Marketing (55.96%)
- Consumer behaviour (15.60%)
- Context (17.43%)
In recent papers he was focusing on the following fields of study:
Anil Bilgihan mostly deals with Marketing, Consumer behaviour, Context, Social psychology and Hospitality.
His Marketing research integrates issues from User-generated content and Investment.
His Investment research is multidisciplinary, incorporating elements of Loyalty business model, Loyalty and Retail industry.
His studies in Consumer behaviour integrate themes in fields like Congruence and Emoticon.
His work carried out in the field of Context brings together such families of science as Social media, Altruism, Service recovery and Compensation.
He interconnects Applied psychology and Helpfulness in the investigation of issues within Social media.
Between 2019 and 2021, his most popular works were:
- The impact of social media activities on brand image and emotional attachment: A case in the travel context (8 citations)
- Attention to Chinese menus with metaphorical or metonymic names: An eye movement lab experiment (5 citations)
- Marketing China to U.S. travelers through electronic word-of-mouth and destination image: Taking Beijing as an example: (2 citations)
In his most recent research, the most cited papers focused on:
- Marketing
- Social psychology
- The Internet
Anil Bilgihan focuses on Social psychology, Context, Marketing, Brand image and Social media.
His work in the fields of Social psychology, such as Altruism and Compensation, overlaps with other areas such as Multilevel model and Hospitality management studies.
In his works, Anil Bilgihan undertakes multidisciplinary study on Context and Beverage industry.
Marketing and Electronic word of mouth are frequently intertwined in his study.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
