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1 – 2 of 2Erik Johansson, Erik Rådman, Hendry Raharjo and Petra Bosch-Sijtsema
This paper aims to identify and prioritize the needs of coworking members. The authors focus on maintaining the existing members rather than attracting new ones.
Abstract
Purpose
This paper aims to identify and prioritize the needs of coworking members. The authors focus on maintaining the existing members rather than attracting new ones.
Design/methodology/approach
The authors use two phases and multiple methods. The first phase focuses on a qualitative approach using observations and interviews to uncover and formulate the members’ needs. The second phase focuses on prioritizing the needs using a quantitative approach.
Findings
The authors discovered 19 member needs from the coworking spaces. Based on an online survey, the authors classified those needs into three main Kano model’s categories.
Originality/value
The resulting member needs and their strategic priorities provide a useful basis for coworking providers to direct their improvement efforts towards achieving greater member satisfaction.
Details
Keywords
Konstantinos Solakis, Vicky Katsoni, Ali B. Mahmoud and Nicholas Grigoriou
This is a general review study aiming to specify the key customer-based factors and technologies that influence the value co-creation (VCC) process through artificial intelligence…
Abstract
Purpose
This is a general review study aiming to specify the key customer-based factors and technologies that influence the value co-creation (VCC) process through artificial intelligence (AI) and automation in the hospitality and tourism industry.
Design/methodology/approach
The study uses a theory-based general literature review approach to explore key customer-based factors and technologies influencing VCC in the tourism industry. By reviewing the relevant literature, the authors conclude a theoretical framework postulating the determinants of VCC in the AI-driven tourism industry.
Findings
This paper identifies customers' perceptions, attitudes, trust, social influence, hedonic motivations, anthropomorphism and prior experience as customer-based factors to VCC through the use of AI. Service robots, AI-enabled self-service kiosks, chatbots, metaversal tourism and new reality, machine learning (ML) and natural language processing (NLP) are technologies that influence VCC.
Research limitations/implications
The results of this research inform a theoretical framework articulating the human and AI elements for future research set to expand the models predicting VCC in the tourism industry.
Originality/value
Few studies have examined consumer-related factors that influence their participation in the VCC process through automation and AI.
Details