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Changing ecosystems with digitalisation, the value of information affects all sub-ecosystems, and due to societal changes, management approaches have started to be implemented. This new administration digitalisation, which is the basis of their strategy, made it mandatory for them to adapt to technology. This article details the theoretical basis of the business ecosystem to investigate the integration of human-computer interaction (HCI) technology and platform business ecosystem into the artificial intelligence (AI) environment and to create practicality for the intellectual development of platform business strategy ecosystem management. Then, in the context of textile e-commerce, the intelligent clothing ecosystem is recommended, and the structure of the smart clothing ecosystem is created. A flexible production planning model with multiple constraints and maximum cost savings has been developed within system constraints and objective function scope. The standard genetic algorithm after optimisation was used to solve the aim of model function (based on double-layer integer coding). In the context of the parameters of the algorithm and textile layout, the algorithm was calculated with the MATLAB simulation tool, and then a textile experiment was carried out to solve the problem of system management. Finally, the audio, interactive customer survey results were analysed with structural equation modelling, and a human-computer interactive customer trust model was proposed. The results indicate that the calculation results of the objective function with 6 order sizes and 40 order sizes tend to be good and that the 6th order, respectively, tends to be good. The Gantt chart, calculated by the optimisation algorithm, can show the equipment selection strategy, start time and end time of each order in different workshops. The combination of each operation planning strategy is the production planning chart that corresponds to the order. It is thought that this study, AI-oriented HCI technology for future studies, can solve the strategic management problem of the platform business ecosystem, realise the efficient ecological functioning of the system and benefit businesses in this context.

This chapter offers an overview of the applications of artificial intelligence (AI) in the textile industry and in particular, the textile colouration and finishing industry. The advent of new technologies such as AI and the Internet of Things (IoT) has changed many businesses and one area AI is seeing growth in is the textile industry. It is estimated that the AI software market shall reach a new high of over US$60 billion by 2022, and the largest increase is projected to be in the area of machine learning (ML). This is the area of AI where machines process and analyse vast amount of data they collect to perform tasks and processes. In the textile manufacturing industry, AI is applied to various areas such as colour matching, colour recipe formulation, pattern recognition, garment manufacture, process optimisation, quality control and supply chain management for enhanced productivity, product quality and competitiveness, reduced environmental impact and overall improved customer experience. The importance and success of AI is set to grow as ML algorithms become more sophisticated and smarter, and computing power increases.

There is clear and robust evidence of the importance of going outdoors to the health and wellbeing of older people. However, modern technologies have enabled more and more of the outside world to be brought inside. Though, it can be hypothesised that this is a poor substitute for literally being outdoors, little is understood as to why this is, not how much of the outdoors could be re-presented indoors to give benefits. This chapter briefly gives examples of how new technologies can bring the outdoors inside and potential advantages of doing that to help older people stay connected to other people and the outside world. It highlights what is still missing from literally engaging with the outdoor world, for example the social connection with other people, random-chance encounters with others, over reliance on visual representation and a lack of control. The absence of the mundane in many of the re-presentations of the outdoor world is also evident and this appears to be important in literal interactions with the outside world. Nevertheless, there appears to be great promise in connecting people to the outside world without literally having to go outdoors, especially for those with mobility impairments who are unable to get out and about.

Purpose – The purpose of this research is to know the influence of manufacture of textiles, clothing, and leather and manufacture of paper, printing, and publishing on economic growth.

Design/Methodology/Approach – The method of research used was a causal research design in North Sumatera Province. The data used are secondary data sourced from Statistics Agency of North Sumatera Province. The method of analysis used in this research is SEM method using software Smart PLS.

Findings – The results show that manufacture of textiles, clothing, and leather and manufacture of paper, printing, and publishing influence to the economic growth.

Research Limitations/Implications – Limitations of the study included not analyzing by data pooling, and samples were restricted only to North Sumatra Province. The implication of this research is that the variables of manufacture of textiles, clothing, and leather give a significant contribution to the economic growth of North Sumatra. To this end, that need to be made some policies shoul be implemented to facilitate manufacture of textiles, clothing, and leather others invest in the district and city in North Sumatra.

Originality/Value – The originality of this study attempts to examine export indicators in certain segments where other studies do not examine them.