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This study aims to examine the causal factors of customer motivation, trust and loyalty, influencing the level of repurchase intentions of local tourists travelling during pandemic COVID-19 crisis in Thailand.

The population of this study comprised all Thai local tourists travelling in Thailand. Using simple random sampling of local tourists on travel in Thailand, quantitative data were collected from 500 tourists as the sampling, representing Northern Thailand, North-Eastern Thailand, Central Thailand, Southern Thailand and Bangkok. Path analysis, including correlation matrix and factor confirmation, was used to test the causal factors influencing the level of repurchase intentions.

Motivation trust, customer trust, customer loyalty and repurchase intentions of Thai domestic tourism were on a high level. In addition, there were positive influences of customer motivation, trust and loyalty on the level of repurchase intentions by local tourists travelling in Thailand.

The study results demonstrate that the social exchange theory can be used to explain the influences of customer motivation, customer trust and loyalty on repurchase intentions of domestic Thai tourism.

Network analysis is a well consolidated research area in several disciplines. Within management and organizational studies, network scholars consolidated a set of research practices that allowed ease of data collection, high inter case comparability, establishment of nomological laws and commitment to social capital motivation. This paper aims to elicit the criticism it has received and highlight the unsettled lacunae.

This paper sheds light on Network Analysis’s breakthroughs, while showing how its scholars innovated by responding to critics, and identifying outstanding debates.

The paper identifies and discusses three streams of criticism that are still outstanding: the role of human agency, the meaning of social ties and the treatment of temporality.

This paper brings to fore current debates within the Network Analysis community, highlighting areas where future studies might contribute.