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The purpose of this paper is to develop a statistical-based model to forecast future domestic water demand in the context of climate change, population growth and technological development in Yellow River.

The model is developed through the analysis of the effects of climate variables and population on domestic water use in eight sub-basins of the Yellow River. The model is then used to forecast water demand under different environment change scenarios.

The model projected an increase in domestic water demand in the Yellow River basin in the range of 67.85 × 10⁸ to 62.20 × 10⁸ m³ in year 2020 and between 73.32 × 10⁸ and 89.27 × 10⁸ m³ in year 2030. The general circulation model Beijing Normal University-Earth System Model (BNU-ESM) predicted the highest increase in water demand in both 2020 and 2030, while Centre National de Recherches Meteorologiques Climate Model v.5 (CNRM-CM5) and Model for Interdisciplinary Research on Climate- Earth System (MIROC-ESM) projected the lowest increase in demand in 2020 and 2030, respectively. The fastest growth in water demand is found in the region where water demand is already very high, which may cause serious water shortage and conflicts among water users.

The simple regression-based domestic water demand model proposed in the study can be used for rapid evaluation of possible changes in domestic water demand due to environmental changes to aid in adaptation and mitigation planning.

The construction sector is notorious for the dichotomy between its intensive use of information in its decision‐making processes and its limited access to, and insufficient use of, the pertinent information that is potentially available, e.g. on the internet. This paper seeks to examine this issue. To solve this problem (the ‘problem of information aboutinformation’), a multidisciplinary team developed an online question‐answering (Q.‐A.)system that uses natural language for the query and the reply. The system provides a direct answer to questions posed by building industry participants, instead of providing a list of references (as is the case with most online information retrieval systems), much as if onewere asking a question of, and receiving a response from, an expert.It has the capabilitiesto process questions in natural language, to find appropriate fragments of answers indifferent web sites and to condense them into a paragraph, also written in natural language. The main features of the system are that it uses domain‐specific knowledge (in the form ofa hierarchical specialized thesaurus complemented by terms of fieldwork parlance),semantic categorization, a database of filtered and indexed web sites, and an online interface that is adapted to different profiles of actors in the construction sector. The testing process shows that the system goes beyond the lists of references and links provided by traditional search engines on the web.The Q.‐A.system already gives 70% of satisfactory answers. The Q.‐A.system can be applied to other business domains apart from information retrieval and decision‐making in the building sector. It is also possible to apply it to the exploitation of in‐house knowledge management database.

This paper examines user generated social media content bearing on consumers’ attitude and belief systems taking the domain of natural food product as illustrative case. This research sheds light on how consumers think and talk about natural food within the context of food well-being and health.

The authors used a keyword-based approach to extract user generated content from Twitter and used both food as well-being and food as health frameworks for analysis of more than two million tweets.

The authors found that consumers mostly discuss food marketing and less frequently discuss food policy. Their results show that tweets regarding naturalness were significantly less frequent in food categories that feature naturalness to an extent, e.g. fruits and vegetables, compared to food categories dominated by technologies, processing and man-made innovation, such as proteins, seasonings and snacks.

This paper provides numerous implications and contributions to the literature on consumer behavior, marketing and public policy in the domain of natural food.

The authors’ exploratory findings can be used to guide food system stakeholders, farmers and food processors to obtain insights into consumers' mindset on food products, novel concepts, systems and diets through social media analytics.

The authors’ results contribute to the literature on the use of social media in food marketing on understanding consumers' attitudes and beliefs toward natural food, food as the well-being literature and food as the health literature, by examining the way consumers think about natural (versus man-made) food using user generated content of Twitter, which has not been previously used.

Posting and sharing about food on social media has surged in popularity amongst younger generations such as Millennials and Generation Z. This study aims to analyse and compare food-tourism sharing behaviour on social media across generations. First, this study specifically investigates the factors influencing the intention to share food experiences on social media; second, it examines the impact of sharing intention on actual behaviour and loyalty; and third, it determines whether Millennials and Generation Z differ in these relationships.

A survey was carried out of Millennial and Generation Z travellers who shared food experiences on social media. Structural equation modelling (SEM) and multi-group analysis were performed to examine the cause-and-effect relationship in both generations.

The findings reveal differences in motivation, satisfaction, sharing intention, sharing behaviour and loyalty between generations (Millennials and Generation Z).

This study contributes to the literature on the antecedents of food-sharing behaviour in online communities by indicating factors that influence the sharing of culinary experiences and brand or destination loyalty across generations. Suggestions for future research include exploring online food-sharing behaviour through cross-cultural comparisons in various regions.

As Millennials and Generation Z will expand their market share in the coming years, the findings of this study can help improve marketing strategies for culinary tourism and generate more intense food experiences for both generations.

The outcome of the research provides new insights to develop a conceptual model of food-sharing behaviour and tourism on social media by drawing comparisons across generations.