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The purpose of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on an algorithm and applying an interpretation of chaos theory developed in the context of General Systems Theory and Big Data.

Tourism is one of the most digitalized sectors of the economy, and social networks are an important source of data for information gathering. However, the high levels of redundant information on the Web and the appearance of contradictory opinions and facts produce undesirable effects that must be cross-checked against real data. This paper sets out the causal relationships associated with tourist flows to enable the formulation of appropriate strategies.

The results can be applied to numerous cases, for example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups, as well as analysing tourist behaviour in terms of the most relevant variables.

The technique presented here breaks with the usual treatment of the tourism topics. Unlike statistical analyses that merely provide information on current data, the authors use orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.

Business process management (BPM) and lean management (LM) are both recognized for improving organizational performance through continuous improvement, yet their similarities and differences have been poorly discussed so far. This paper aims to find their main differences and similarities using a systematic method for literature review.

The paper uses a structured literature review known as SYSMAP (Scientometric and sYStematic yielding MApping Process). The method integrates bibliometrics and content analysis procedures to perform in-depth analysis of the literature at hand.

Both methodologies seek continuous improvement with focus on the customer and process standardization, but they are divergent mainly in relation to the flow they intend to improve. The impossibility of implementing both methodologies in an effective way was also observed, mainly due to the differences they present in relation to how to achieve the continuous improvement cycle.

As any other literature reviews, the major limitation is to have omitted relevant literature even though all available procedures have been used to avoid this situation.

This paper offers a novel perspective from the practitioner side. LM may be better used in human-intensive process improvement whereas BPM in technology-intensive ones. Such characteristics open up new opportunities for practitioners aiming at integrating both approaches.

This is the first paper that systematically analyses the body of literature of BPM and LM with the means to better understand their similarities and differences.