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Double auctions are widely used market mechanisms on the world. Communication technologies such as internet increased importance of this market institution. The purpose of this study is to develop novel bidding strategies for dynamic double auction markets, explain price formation through interactions of buyers and sellers in decentralized fashion and compare macro market outputs of different micro bidding strategies.

In this study, two novel bidding strategies based on fuzzy logic are presented. Also, four new bidding strategies based on price targeting are introduced for the aim of comparison. The proposed bidding strategies are based on agent-based computational economics approach. The authors performed multi-agent simulations of double auction market for each suggested bidding strategy. For the aim of comparison, the zero intelligence strategy is also used in the simulation study. Various market outputs are obtained from these simulations. These outputs are market efficiencies, price means, price standard deviations, profits of sellers and buyers, transaction quantities, profit dispersions and Smith’s alpha statistics. All outputs are also compared to each other using t-tests and kernel density plots.

The results show that fuzzy logic-based bidding strategies are superior to price targeting strategies and the zero intelligence strategy. The authors also find that only small number of inputs such as the best bid, the best ask, reference price and trader valuations are sufficient to take right action and to attain higher efficiency in a fuzzy logic-based bidding strategy.

This paper presents novel bidding strategies for dynamic double auction markets. New bidding strategies based on fuzzy logic inference systems are developed, and their superior performances are shown. These strategies can be easily used in market-based control and automated bidding systems.

The purpose of the study is to measure the performance level of halal compliance practices by the halal-certified restaurants in Malaysia and rank and rate them based on several dimensions of halal compliance.

A total of 320 halal restaurants were surveyed. The absolute measurement approach of the analytic hierarchy process (AHP) was applied to rank and rate the restaurants. Finally, ANOVA and independent t-test were applied to assess if there is any significant difference in halal compliance performance between different groups of the respondents.

The AHP application resulted in only 19 restaurants (5.94%) achieving an “Excellent” rating. A significant difference has been observed between different groups of the respondents regarding their halal compliance performance.

An onsite audit and ranking of all the restaurants in Malaysia were beyond the scope of the study. The research was able to rank only 320 restaurants across Malaysia.

The findings and methodology of the study will provide policymakers with a clear roadmap for establishing a comprehensive rating system in the fields of the halal food industry to enhance the quality and integrity of the halal food management system.

To the best of the authors’ knowledge, this is the first time an empirical approach, like AHP, has been used to determine how Malaysia’s halal-certified restaurants stack up against one another. Similar studies can be carried out in other sectors of the halal industry as well as in similar context.

Developments regarding the use of artificial intelligence (AI) in transportation systems, one of the important stakeholders of tourism, are remarkable. However, no review thus far has provided a comprehensive overview of research on AI in transportation systems.

To fill this gap, this study uses the VOSviewer software to present a bibliometric review of the current scientific literature in the field of AI-related tourism research. The theme of AI in transportation systems was explored in the Web of Science database.

The original search yielded 642 documents, which were then filtered by parameters. For publications related to AI in transportation systems, the most cited documents, leading authors, productive countries, co-occurrence analysis of keywords and bibliographic matching of documents were examined. This report shows that there has been a recent increase in research on AI in transport systems. However, there is only one study on tourism. The country that contributed the most is China with 298 studies. The most used keyword in the documents was intelligent transportation system.

The bibliometric analysis of the existing work provided a valuable and seminal reference for researchers and practitioners in AI-related in transportation system.