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Aligning corporate communications through different information sources is a great challenge for marketers, especially those operating in the tourism sector, which has been harshly affected by the recent COVID-19 pandemic. This paper provides a deep analysis of the implementation of seven basic principles of the integrated marketing communications (IMC) paradigm in a crisis situation.

In-depth interviews with tourism and hospitality service providers were conducted in the fourth quarter of 2021 in Croatia, a destination that showed remarkable results in terms of the number of international tourist arrivals during the pandemic.

Most firms successfully transitioned from tactical to strategic IMC implementation. Some problems were reported in the coordination of communication tools and channels. Whereas the use of digital technology was enhanced, database management did not receive sufficient attention. Message clarity represented the greatest challenge, while consumer-centric communication was the most neglected principle. Relationship building was pursued mainly through B2B rather than B2C communication, whereas brand equity development pursued through communication mix mostly focused on increases in awareness, perceived quality and attitudinal loyalty.

This research is qualitative in nature and provides opinions on IMC adoption from the managerial perspective only.

This paper provides guidelines for the successful integration of marketing communications (marcom) in an extremely ambiguous and uncertain environment.

The contribution of this work lies in the proposal of a new refined and expanded theoretical framework of IMC principles and numerous marcom strategies for operating during the COVID-19 pandemic, thus providing relevant implications for academia and industry.

The purpose of this paper is to present the author’s method of conservative load spectrum (LS) derivation and close-proximity LS extrapolation applying a correction for measurement uncertainty caused by too low sampling frequency or signal noise, which may affect the load histories collected during the flying session and cause some recorded load increments to be lower than the actual values.

Having in mind that the recorded load signal is burdened with some measurement error, a conservative approach was applied during qualification of the recorded values into 32 discrete load-level intervals and derivation of 32 × 32 half-cycle arrays. A part of each cell value of the half-cycle array was dispersed into the neighboring cells placed above by using a random number generator. It resulted in an increase in the number of load increments, which were one or two intervals higher than those resulting from direct data processing. Such an array was termed a conservative clone of the actual LS. The close-proximity approximation consisted of multiplication of the LSs clones and their aggregation. This way, the LS for extended time of operation was obtained. The whole process was conducted in the MS Excel environment.

Fatigue life calculated for a chosen element of aircraft structure using conservative LS is about 20%–60% lower than for the actual LS (depending on the applied value of dispersion coefficients used in the procedure of LSs clones generation). It means that such a result gives a bigger safety margin when operational life of the aircraft is estimated or when the fatigue test for an extended operational period is programed based on a limited quantity of data from a flying session.

This paper presents a proposal for a novel, conservative approach to fatigue life estimation based on the short-term LS derived from the load signal recorded during the flying session.

This study aims to explore spectators' awareness of and attitudes toward sponsoring firms as well as to propose a model predicting their purchase and word-of-mouth (WOM) intentions toward the sponsors of a major sporting event during a pandemic crisis.

A quantitative method was used to collect the data, with 1,259 questionnaires being effectively collected and analyzed using SPSS and AMOS. Exploratory factor analysis (EFA), confirmatory factor analysis (CFA), path analysis and structural equation modeling (SEM) were used to analyze the data.

Factors such as sports involvement, sincerity, social media use, beliefs about sponsorship, sponsor's image, Covid-19 beliefs and emotions, awareness of and attitude toward sponsors were found to significantly predict spectators' purchase and WOM intentions.

The results support the structural equation model, providing a multidisciplinary conceptual framework that highlights the significance of comprehending the role of significant factors in sponsorship efficiency during the Covid-19 crisis. The proposed framework adds to the knowledge corpus of this field.

The purpose of this paper is to present investigations on the significant influence of the tube material and fin density on fluid elastic instability and vortex shedding in a parallel triangular finned tube array subjected to water cross flow.

The experiment was conducted on finned tube arrays with a fin height of 6 mm and fin density of 3 fins per inch (fpi) and 9 fpi. A dedicated setup has been developed to examine fluid elastic instability and vortex shedding. Nine parallel triangular tube arrays with a pitch to tube diameter ratio of 1.78 were considered. The plain tube arrays, coarse finned tube arrays and fine finned tube arrays each of steel, copper and aluminium materials were tested. Plain tube arrays were tested to compare the results of the finned tube arrays having an effective tube diameter same as that of the plain tube.

A significant effect of fin density and tube material with a variable mass damping parameter was observed on the instability threshold. In the parallel triangular finned tube array subjected to water cross flow, a delay in the instability threshold was observed with an increase in fin density. For steel and aluminium tube arrays, the natural frequency is 9.77 Hz and 10.38 Hz, which is close to each other, whereas natural frequency of the copper tubes is 7.40 Hz. The Connors’ stability constant K for steel and aluminium tube arrays is 4.78 and 4.87, respectively, whereas it is 5.76 for copper tube arrays, which increases considerably compared to aluminum and steel tube arrays. The existence of vortex shedding is confirmed by comparing experimental results with Owen’s hypothesis and the Strouhal number and Reynolds number relationship.

This paper’s results contribute to understand the effect of tube materials and fin density on fluid elastic instability threshold of finned tube arrays subjected to water cross flow.

This paper aims to provide researchers and practitioners with a consumer-focused alternative for considering the integration of artificial intelligence (AI) into services.

The paper reviews and critiques the most popular frameworks for addressing AI in service. It offers an alternative approach, one grounded in social psychology and leveraging influential concepts from management and human–computer interaction.

The frameworks that dominate discourse on this topic (e.g. Huang and Rust, 2018) are fixated on assessing technology-determined feasibility rather than consumer-granted permissibility (CGP). Proposed is an alternative framework consisting of three barriers to CGP (experiential, motivational and definitional) and three responses (communicate, motivate and recreate).

The implication of this research is that consistent with most modern marketing thought, researchers and practitioners should approach service design from the perspective of customer experience, and that the exercise of classifying service occupation tasks in terms of questionably conceived AI intelligences should be avoided.

Indicative of originality, this paper offers an approach to considering AI in services that is nearly the polar opposite of that widely advocated by e.g., Huang et al., (2019); Huang and Rust (2018, 2021a, 2021b, 2022b). Indicative of value is that their highly cited paradigm is optimized for predicting the rate at which AI will take over service tasks/occupations, a niche topic compared to the mainstream challenge of integrating AI into service offerings.