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The purpose of this paper is to analyse the impact of Andalusia’s tourism promotion budgets and the efficiency of its campaigns from 2010 to 2022.

A mixed-methods approach is used. Tourism promotion budgets from 2010 to 2022 were measured as a supply indicator. Demand indicators (e.g. airport’s passenger arrivals, number of tourists and hotel occupancy rate) are analysed to measure tourism promotion budget impacts on them.

Tourism promotion budgets are a priority to stimulate tourism demand for Andalusia in times of uncertainly, and promotion campaigns are pivotal to attract and convert potential customers into actual tourists. Moreover, findings reveal that tourism promotion budgets had positive impacts on tourism demand. Whereas tourism promotion campaigns such as “Andalucía wants you back”, “Intensely”, Fitur, World Travel Market, ITB Berlin events and tourism advertising through digital channels have helped to improve tourism demand in Andalusia, ignoring the effects of the COVID-19 pandemic in the year 2020.

This study emphasizes how tourism promotion budgets and promotion campaigns must be constantly monitored by destination marketing organizations to measure the efficiency and effectiveness of assigned economic budgets and its return on investment.

The objective of this study is to investigate the impact of the COVID-19 pandemic on the consumer payment behavior in Italy by correlating financial literacy with digital payment awareness, examining media anxiety and financial security, and including a gender analysis.

Consumers’ attitudes toward cashless payments were investigated using an online survey conducted from November 2021 to February 2022 on a sample of 836 Italian citizens by considering the behavioral characteristics and aspects of financial literacy. Structural equation modeling (SEM) was used to test the hypotheses and to determine whether the model was invariant by gender.

The analysis showed that the fear of contracting COVID-19 and the level of financial literacy had a direct influence on the payment behavior of Italians, which was completely different in its weighting. Fear due to the spread of news regarding the pandemic in the media indirectly influenced consumers’ noncash attitude. The preliminary results of the gender multigroup analysis showed that cashless payment was the same in the male and female subpopulations.

This research is noteworthy because of its interconnected examination. It examined the effects of the COVID-19 pandemic on people’s payment choices, assessed their knowledge, and considered the influence of media-induced anxiety. By combining these factors, the study offered an analysis from a gender perspective, providing understanding of how financial behaviors were shaped during the pandemic.

This study explores the pioneering approach of utilising machine learning (ML) models and integrating social media data for predicting tourist arrivals in Sri Lanka.

Two sets of experiments are performed in this research. First, the predictive accuracy of three ML models, support vector regression (SVR), random forest (RF) and artificial neural network (ANN), is compared against the seasonal autoregressive integrated moving average (SARIMA) model using historical tourist arrivals as features. Subsequently, the impact of incorporating social media data from TripAdvisor and Google Trends as additional features is investigated.

The findings reveal that the ML models generally outperform the SARIMA model, particularly from 2019 to 2021, when several unexpected events occurred in Sri Lanka. When integrating social media data, the RF model performs significantly better during most years, whereas the SVR model does not exhibit significant improvement. Although adding social media data to the ANN model does not yield superior forecasts, it exhibits proficiency in capturing data trends.

The findings offer substantial implications for the industry's growth and resilience, allowing stakeholders to make accurate data-driven decisions to navigate the unpredictable dynamics of Sri Lanka's tourism sector.

This study presents the first exploration of ML models and the integration of social media data for forecasting Sri Lankan tourist arrivals, contributing to the advancement of research in this domain.

This research finds out to what extent companies’ names are influenced by the place’s attributes versus the official branding policies of a place and, consequently, whether and how local companies “buy into” the place’s strategies put forth by official bodies.

This paper is both conceptual and empirical, as a mixed quantitative and interpretive approach is used. The companies’ names of a tourist industry (the tour and guiding companies) in three destinations are compared and pitched against the branding of these cities. The companies' names are classified into categories to ascertain whether they reflect (or diverge from) the official strategies. Finally, a conceptual model is developed to explain the findings: the strategic naming model (SNM).

Our main finding is that the overall business features of a place being stronger determinants to the naming strategies than tourist destination branding initiatives. The intrinsic features of a place seem thus to be “above” destination branding policies. The researched features account for different naming strategies, such as highly original names, flat names or non-strategic names.

As the work is based on a convenience sample, it cannot claim strong representativity. The fact that each of the three data sets was processed by a different researcher might bring up personal biases.

This work is a call for a more intensive use of naming strategies to the companies’ advantages, as naming is found out to be strategy used to a very low degree. Thanks to this research, companies will understand the different naming possibilities and be able to apply them to their strategies by choosing names which express “uniqueness” or “belonging”. Practitioners will also be aware of whether they are communicating towards the industry or towards the market.

No works were found that empirically pursue our research goals. Therefore, this research might be considered as a novelty. The proposed SNM model explains and relates the most usual company naming techniques, which were unrelated up to date.

This paper examines how different configurations of societal impact are pursued by purpose-driven organizations (PDOs) and how these configurations align with the application of varying supply chain design (SCD) practices.

This multi-method study uses quantitative data from 1588 B Corps and qualitative data from 316 B Corps to examine how PDOs align SCD with the pursuit of diverse types of societal impact. The authors first conduct a cluster analysis to group organizations based on the impact they create. Second, qualitative content analysis connects impact with enabling SCD elements.

The analysis of the five identified clusters provides detailed empirical insights on influencers, design decisions and building blocks adopted by PDOs to drive a range of societal impacts. Specifically, the nature of the impact pursued affects (1) whether a PDO will be more influenced by a need in the political environment or an opportunity in the industry environment, (2) the relative importance of the design of social flows versus material flows and (3) the need to develop new relational resources with beneficiaries versus leveraging existing capabilities to manage inter-firm processes.

This study responds to calls to disaggregate different dimensions of societal impact and examines the relationship between SCD and a breadth of sustainability impacts for different stakeholders. In doing so, the authors identify four SCD pathways organizations can follow to achieve specific societal impacts. This study is also the first to employ a supply chain perspective in the study of certified B Corps.

With rapidly changing marketing landscape, nowadays, the formulation of various marketing strategies is increasingly focused on how consumers tend to make decisions. To meet the highly demanding consumer expectations, market segmentation can be used as an important marketing strategy. Due to gender marketing concept familiarity in the contemporary world, gender difference is one of the reference features in the process of market segmentation for marketers. This research is aimed to examine various determining factors that foster consumer purchase decision-making and the differences between consumers of different genders while making shopping and purchase decisions with special reference to an emerging economy, i.e. Pakistan.

Based on a cross-sectional sample of 367 consumers, the study adapted Sproles and Kendall's (1986) Consumer Style Inventory (CSI) to scrutinize the decision-making of both genders in Pakistan. For data analysis, the exploratory and confirmatory factor analysis in addition to the structural equation modeling has been used.

The study emphasized that, with the exception of quality awareness, brand consciousness, fashion consciousness, option overload and price consciousness greatly affect buying decisions. In addition, when it comes to consumer purchase decision-making, significant gender variations were discovered for both fashion consciousness and price consciousness.

Drawing upon the distinctive cultural characteristics of Pakistan and its people, in-depth research was conducted on purchasing behaviors of Pakistani consumers and the decision-making characteristics of customers of different genders were summarized. The outcomes are expected to make a significant contribution to the field of gender marketing by organizations.

While extant research has increasingly examined minority entrepreneurs, less attention has been paid to Eastern European immigrant entrepreneurs and the role that marketing agility and risk propensity play in their resilience and survival in Nordic countries. This paper aims to highlight the importance of these factors for Eastern European immigrant entrepreneurs in the developed Nordic economy of Denmark.

This paper adopts the dynamic capabilities view as a theoretical framework and uses a qualitative research approach with interviews as the main data collection method. The empirical sample comprises 12 entrepreneurs originating from Hungary, Slovakia, Latvia, Lithuania and Romania, who operate in Denmark.

The findings show that contrary to prior studies that have highlighted a reliance among the migrant entrepreneurial community on ethnic networks as their dominant target market, Eastern European immigrant entrepreneurs located in Denmark, in contrast, focused on attracting Danish consumers as their target market audience. Leveraging multiple networks was therefore found to be critical to the survival of these immigrant ventures. Additionally, the entrepreneurs' marketing agility, underpinned by their optimistic approach, growth ambitions and passion for entrepreneurship, was found to play a pivotal role in their survival. Finally, despite the stable institutional environment in Denmark and the ease of doing business (both of which are influential factors in shaping the risk propensity and risk perception of entrepreneurs), the authors found immigrant entrepreneurs' risk propensity to be rather low, which was contrary to the expectations.

The current paper is one of the first studies that explicitly analyzes the roles of marketing agility and risk propensity in the resilience and survival of the ventures of relatively skilled immigrant entrepreneurs from Eastern Europe in a developed Nordic economy (Denmark). The paper's findings also challenge the notion associated with immigrant entrepreneurial ventures being primarily focused on ethnic customers or enclaves. The paper also specifies the peculiarities of marketing agility in immigrant entrepreneurial contexts and solidifies the importance of diverse networks in immigrant business survival and development.

This study addresses the pivotal role of digital transformation (DT) in the post-pandemic business landscape, identifying a notable gap in comprehending strategic adaptations and digital communication amidst the complexities of the digital era. It seeks to illuminate practical insights for businesses navigating through DT by intertwining its technological and organizational aspects.

Employing a conceptual approach, this paper synthesizes existing literature and theoretical frameworks related to DT, integrating its technological, strategic and organizational dimensions. It utilizes real-world instances to elucidate the digital era’s practical implications and strategic adaptations. The study also proposes a research agenda that spotlights pressing DT issues, challenges and actionable strategies for businesses.

Despite DT’s inherent complexity, the paper reveals that it is crucial for businesses navigating the contemporary digital landscape. It underscores the importance of strategic adaptations in DT, highlighting their implications on customer experiences and organizational structures amidst the evolving technological and market dynamics. Moreover, it accentuates the significance of effective digital communication strategies in enhancing user experiences and conveying value propositions adeptly.

This paper brings vital aspects of DT impacting modern organizations, offering invaluable insights for practitioners and scholars aiming to comprehend and navigate DT’s complexities. The identified research gaps underscore the necessity for further exploration, aiming to broaden DT’s theoretical and practical facets.

This study aims to examine the multidimensional nature of institutional distance as a driver of acquisition decisions in emerging markets. Then, this study aims to offer a nuanced perspective on the role of its various formal and informal dimensions by taking into account the potential contingency role played by a firm’s context experience.

Building on institutional economics and organizational institutionalism, this study explores the heterogeneity of institutional distance and its effects on the decision to enter emerging versus advanced markets through cross-border acquisitions. Thus, institutional distance is disentangled into its formal and informal dimensions, the former being captured by regulatory efficiency, country governance and financial development. Furthermore, our framework examines the moderating effect of an acquiring firm’s experience in institutionally similar environments, defined as context experience. The hypotheses are analyzed on a sample of 496 cross-border acquisitions by Italian companies in 41 countries from 2008 to 2018.

Findings indicate that at an increasing distance in terms of regulatory efficiency and financial development, acquiring firms are less likely to enter emerging markets, while informal institutional distance is positively associated with such acquisitions. Context experience mitigates the negative effect of formal distance and enhances the positive effect of informal distance.

This study contributes to institutional distance literature in multiple ways. First, by bridging institutional economics and organizational institutionalism and second, by examining the heterogeneity of formal and informal dimensions of distance, this study offers a finer-grained perspective on how institutional distance affects acquisition decisions. Finally, it offers a contingency perspective on the role of context experience.

The purpose of this paper is to identify the potential and the challenges for different firms in adopting an AI-first strategy. The study attempts to discern if any company can prioritize AI at the forefront of their strategic plans.

Drawing from illustrative examples from well-known AI-leaders like Netflix and Spotify, as well as from upcoming AI startups and industry incumbents, the paper explores the strategic role of AI in core business processes and customer value creation. It also discusses the advent and implications of generative AI tools since late 2022 to firms’ business strategies.

The authors identify three types of AI-first strategies, depending on firms’ starting points: digital tycoon, niche carver and asset augmenter. The authors discuss how each strategy can aim to achieve data, algorithmic and execution advantages, and what the strategic bottlenecks and risks are within each strategy.

To the best of the authors’ knowledge, this paper is the first to systematically describe how companies can form “AI-first” strategies from different starting points. This study includes actionable examples from known industry players to more emerging startups and industrial incumbents.