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The benefits of artificial intelligence (AI) related technologies for manufacturing firms are well recognized, however, there is a lack of industrial AI (I-AI) maturity models to enable companies to understand where they are and plan where they should go. The purpose of this study is to propose a comprehensive maturity model in order to help manufacturing firms assess their performance in the I-AI journey, shed lights on future improvement, and eventually realize their smart manufacturing visions.

This study is based on (1) a systematic review of literature on assessing I-AI-related technologies to identify relevant measured indicators in the maturity model, and (2) semi-structured interviews with domain experts to determine maturity levels of the established model.

The I-AI maturity model developed in this study includes two main dimensions, namely “Industry” and “Artificial Intelligence”, together with 12 first-level indicators and 35 second-level indicators under these dimensions. The maturity levels are divided into five types: planning level, specification level, integration level, optimization level, and leading level.

The maturity model integrates indicators that can be used to assess AI-related technologies and extend the existing maturity models of smart manufacturing by adding specific technical and nontechnical capabilities of these technologies applied in the industrial context. The integration of the industry and artificial intelligence dimensions with the maturity levels shows a road map to improve the capability of applying AI-related technologies throughout the product lifecycle for achieving smart manufacturing.

The purpose of this paper is to improve the understanding of the factors influencing the success of digital transformation (DT) and problems/challenges in DT as well as the communication methods used to involve citizens, based on a systematic literature review of research articles about citizen involvement in DT published between January 2010 and May 2021.

After establishing inclusion and exclusion criteria, a systematic review of relevant studies was conducted. Out of a total of 547 articles, 33 met the paper selection criteria.

The analysis of the included 33 empirical studies reveals that the factors influencing the success of DT can be described as the opposite side from challenges and problems in DT. These factors and challenges/problems all influence DT and they can be grouped into organisational values, management capabilities, organisational infrastructure, and workforce capabilities. The communication methods for citizen involvement in DT include: (1) communication mediated by human, (2) communication mediated by computers, and (3) mixed communication methods.

The study identified specific factors that influence DT supported by citizen involvement, at a more fine-grained level. The findings concerning communication methods extend related studies for citizen involvement by adding town hall meetings and communication methods mediated by computers. Furthermore, this study links the research findings to develop a framework for citizen involvement in DT, assisting in better selecting communication methods to involve citizens for addressing problem areas in DT.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2022-0237

This paper gathers tourism digital footprint from online travel platforms, choosing social network analysis method to learn the structure of destination networks and to probe into the features of tourist flow network structure and flow characteristics in Guilin of China.

The digital footprint of tourists can be applied to study the behaviors and laws of digital footprint. This research contributes to improving the understanding of demand-driven network relationships among tourist attractions in a destination.

(1) Yulong River, Yangshuo West Street, Longji Terraced Fields, Silver Rock and Four Lakes are the divergent and agglomerative centers of tourist flow, which are the top tourist attractions for transiting tourists. (2) The core-periphery structure of the network is clearly stratified. More specifically, the core nodes in the network are prominent and the core area of the network has weak interaction with the peripheral area. (3) There are eight cohesive subgroups in the network structure, which contains certain differences in the radiation effects.

This research aims at exploring the spatial network structure characteristics of tourism flows in Guilin by analyzing the online footprints of tourists. It takes a good try to analyze the application of network footprint with the research of tourism flow characteristics, and also provides a theoretical reference for the design of tourist routes and the cooperative marketing among various attractions.

This study aims to explore the influence of risk preference and information acquisition on outdoor tourism safety decision-making.

Five hundred twenty outdoor tourists were surveyed, and data were analyzed using two-stage regression.

Risk preference positively affects tourists’ safety decisions for outdoor travel. The greater the risk preference is, the more likely the tourists are to make the risky decision of outdoor tourism. Information acquisition significantly negatively affects tourists’ safety decisions for outdoor tourism. Tourists who obtain information through social channels are more likely to make safer travel decisions than those who do not.

Risk preference and information acquisition are introduced into outdoor tourism safety research.