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The link between confidence and economic decisions has been widely covered in the economic literature, yet it is still an unexplored field in tourism. The purpose of this paper is to address this gap, and investigate benefits in forecast accuracy that can be achieved by combining the UNWTO Tourism Confidence Index (TCI) with statistical forecasts.

Research is conducted in a real-life setting, using UNWTO unique data sets of tourism indicators. UNWTO TCI is pooled with statistical forecasts using three distinct approaches. Forecasts efficiency is assessed in terms of accuracy gains and capability to predict turning points in alternative scenarios, including one of the hardest crises the tourism sector ever experienced.

Results suggest that the TCI provides meaningful indications about the sign of future growth in international tourist arrivals, and point to an improvement of forecast accuracy, when the index is used in combination with statistical forecasts. Still, accuracy gains vary greatly across regions and can hardly be generalised. Findings provide meaningful directions to tourism practitioners on the use opportunity cost to produce short-term forecasts using both approaches.

Empirical evidence suggests that a confidence index should not be collected as input to improve their forecasts. It remains a valuable instrument to supplement official statistics, over which it has the advantage of being more frequently compiled and more rapidly accessible. It is also of particular importance to predict changes in the business climate and capture turning points in a timely fashion, which makes it an extremely valuable input for operational and strategic decisions.

The use of sentiment indexes as input to forecasting is an unexplored field in the tourism literature.

Bulk shipping mostly facilitates the smooth flow of raw materials around the globe. Regardless, forecasting a bulk shipbuilding orderbook is a seldom researched domain in the academic arena. This study aims to pioneer an econophysics approach coupled with an autoregressive data analysis technique for bulk shipbuilding order forecasting.

By offering an innovative forecasting method, this study provides a comprehensive but straightforward econophysics approach to forecast new shipbuilding order of bulk carrier. The model has been evaluated through autoregressive integrated moving average analysis, and the outcome indicates a relatively stable good fit.

The outcomes of the econophysics model indicate a relatively stable good fit. Although relevant maritime data and its quality need to be improved, the flexibility in refining the predictive variables ensure the robustness of this econophysics-based forecasting model.

By offering an innovative forecasting method, this study provides a comprehensive but straightforward econophysics approach to forecast new shipbuilding order of bulk carrier. The research result helps shipping investors make decision in a capital-intensive and uncertainty-prone environment.

This article examines the creation of an accurate market projection designed with easy-to-use, cost-effective data analytic techniques. Many of the techniques explored are derived from the subdisciplines of decision support and data warehousing found in the information technology arena. Two significant contributions are presented: a simple mathematical technique that eliminates the need for heuristics, and the simplification of the process to the point where no computer or sophisticated statistical analysis is needed.

The purpose of this paper is to investigate and clarify “irrationality” problem through the maritime industry practices and leading incentives behind common investors.

This paper includes a review of broader business and economics literature; review of shipping business practices and detection of institutional pathways and misleading mechanisms behind the irrational preferences; investigation of data (for some arguments); and introduction of a theoretical approach.

There are several industry practices and norms well established and followed by decision makers, which may cause and initiate illogical and irrational (long-run) preferences. Short-termism is an erroneous habit of common shipping investors, which is embedded and forced through traditional financial math (i.e. discounted cash flow), financial system (e.g. initial public offerings with high-frequency transactions, interest rate governance and asset valuation mechanism) or flawed contracting tradition (i.e. commission bias).

Both shipping business and financial institutions need to redesign their working mechanisms, evaluation systems, risk detection and assessment procedures. As discussed in Section 4.7, commission-based (float) services must be converted to regular flat rate payments with long-term contracts to protect investors from rational choices of intermediaries in the short-run which encourages investor’s irrationality. Having a long-term service contract will also improve sustainability of intermediaries and lower their business risk (win-win).

The impact of this paper is two-fold. First, it raises critical questions about professional decay and drawbacks of some traditional instruments in the shipping business. For the first time, this paper emphasises on various challenges which deteriorate credibility of the industry and causes ill-defined investments. Some arguments have extreme priority for strengthening the foundations of the industry. Second, this paper establishes a new stream of scholarly research highlighting weaknesses of conventional economic approach and demand for outsourcing other schools of economics (e.g. institutional and behavioural) into the shipping business.

A decade after Powell et al.’s (2011) seminal article on behavioral strategy, which called for models to solve real-world problems, the authors revisit the field to ask whether behavioral strategy is coming of age. The purpose of this paper is to explain how behavioral strategy can and has been used in real-world settings.

This study presents a conceptual review with case study examples of the impact of behavioral strategy on real-world problems.

This study illustrates several examples where behavioral strategy debiasing has been effective. Although no causal claims can be made, with the stark contrast between the negative impact of biased strategies and the positive results emerging from debiasing techniques, this study argues that there is evidence of the benefits of a behavioral strategy mindset, and that this should be the mindset of a responsible strategic leader.

This study presents a demonstration of analytical, debate and organizational debiasing techniques and how they are being used in real-world settings, specifically military intelligence, Mergers and acquisitions deal-making, resource allocation and capital projects.

Behavioral strategy has broad application in private and public sectors. It has proven practical value in various settings, for example, the application of reference class forecasting in large infrastructure projects.

A conceptual review of behavioral strategy in the wild.

This study aims to explain the facts about behavioral biases that cannot be explained by rational patterns in ship investments of small-size shipping companies.

A qualitative approach was adopted in this study. The systematic approach of Wolcott (1994) and the action flows proposed by Miles and Huberman (1994) were taken into consideration.

Factors affecting ship investments are classified as ship finance, market timing, ship specifications and profile and business models of ship investors. In addition, behavioral biases that stand out under each theme are explained in the light of behavioral finance literature.

The originality of this study rests on the lack of studies on behavioral aspects of ship investments.