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The Astroworld concert tragedy is used as an example of crisis (mis)management and the potential utility of the 4R model. Although the 4R model has been implemented in high-risk emergency management situations, it is useful in the PR field because of its actionable approach, creating a way for practitioners to prepare for and manage crisis situations.

This is an analysis of the crisis that occurred at Astroworld, spanning preparation, day-of events, casualties and enduring reputational impact. The paper applies the 4R method to the Astroworld tragedy to show how it could have lessened or even prevented the tragedy. Finally, the SCCT model is used to explain why the official post-crisis statements were ineffective.

Social media has heightened the importance of a quick and effective organizational response to risk and crisis situations because poor responses can go viral quickly. However, social media also provides intelligence and crowd sourced information that can inform PR practitioners of emerging crisis scenarios. It is also an underutilized tool for two-way communication during crises.

The 4R approach is beneficial to general practitioners as it simplifies crisis best-practices, something essential for quick action. As our world changes and becomes less predictable, practitioners must have a clear plan to protect their organizations and the public surrounding them. This approach includes reduction, readiness, response and recovery, which are all essential in crisis communication.

The 4R method has not been explored or applied in the PR field. This paper highlights how the model has been utilized in the emergency management field and illustrates the way 4R can serve the PR field.

This study seeks to explore the intricate relationship among supply chain transparency, digitalization and idiosyncratic risk, with a specific focus on newly public firms. The objective is to determine whether supply chain transparency effectively mitigates idiosyncratic risk within this context and to understand the potential impact of digitalization on this dynamic interplay.

The study utilizes data from Initial Public Offerings (IPOs) on China’s Growth Enterprise Board (ChiNext) over the last five years, sourced from the CSMAR database and firms’ annual reports. The research covers the period from 2009 to 2021, observing each firm for five years post-IPO. The final sample comprises 2,645 observations from 529 firms. The analysis employs the Hausman test, considering the panel-data structure of the sample and favoring fixed effects over random effects. Additionally, it applies the high-dimensional fixed effects (HDFE) estimator to address unobserved heterogeneity.

The analysis initially uncovered an inverted U-shaped relationship between supply chain transparency and idiosyncratic risk, indicating a delicate equilibrium where detrimental effects diminish and beneficial effects accelerate with increased transparency. Moreover, this inverted U-shaped relationship was notably more pronounced in newly public firms with a heightened level of firm digitalization. This observation implies that firm digitalization amplifies the impact of transparency on a firm’s idiosyncratic risk.

This study distinguishes itself by providing distinctive insights into supply chain transparency and idiosyncratic risk. Initially, we introduce and substantiate an inverted U-shaped correlation between supply chain transparency and idiosyncratic risk, challenging the conventional linear perspective. Secondly, we pioneer the connection between supply chain transparency and idiosyncratic risk, especially for newly public firms, thereby enhancing comprehension of financial implications. Lastly, we pinpoint crucial digital conditions that influence the relationship between supply chain transparency and idiosyncratic risk management, offering a nuanced perspective on the role of technology in risk management.

This empirical paper investigates how entrepreneurial firms change their business models in the context of internationalization by identifying different forms of business model innovation (BMI) and exploring the interrelationship between BMI and internationalization.

Based on the dynamic states approach of entrepreneurship (Levie and Lichtenstein, 2010), this paper analyses primary and secondary data from nine European firms following a multiple case study approach.

This paper presents four patterns of radical change and eight types of incremental adaption with-in business models in the context of internationalization. We describe these BMI patterns and types, and we also show how they contribute to increasing involvement in international business activities and the internationalization-related triggers that might cause them.

This paper contributes to a better understanding of the BMI process in the course of internationalization. It also highlights the complex interrelationship between BMI and internationalization by building on a progressive theoretical approach.

This study aims to analyze the importance and performance of customer-facing technologies in luxury hotels. The study also assessed differences between and within the four generations in the importance-performance analysis (IPA).

Data were collected using a Qualtrics panel of recent luxury hotel customers in the USA belonging to all four generations. The cross-generational IPA was conducted using t-tests and (ANAOVA).

The IPA matrix concentrated most technology items in either low importance – low performance or high importance – high performance quadrants. One-way ANOVA revealed significant differences between generations on the importance ratings of all technology items except wireless charging power solutions and on the performance ratings of all technology items. Furthermore, post hoc tests indicated that millennials rated luxury technology most favorably among the four cohorts, followed by generations Z, X and Baby Boomers. In addition, significant differences between the importance and performance of many technology items within each generational cohort were observed. Overall, Wi-Fi was unanimously ranked across generations as the most important technology among luxury guests, but it was the only one that scored lower in performance than importance.

The findings of this study contribute to hospitality scholarship in two primary ways: the importance and performance of technology and generational differences. The results advance the understanding of the impact of generational factors on customer-facing technological adoptions in the luxury hotel sector.

Technologies that are pervasive in the home also become vital offerings for hotels. The more pervasive technology, the more a luxury hotel must work to ensure that it performs at optimal levels. Additionally, which technologies are most important to targeted generations are provided so practitioners may budget for their implementation.

This research is a pivotal step forward in unraveling the intricate interplay between generational factors and technological evaluations, providing a foundation for future research and practical applications in a rapidly evolving technological landscape in the hospitality industry.

This paper provides practical advice for archaeologists and heritage specialists wishing to use ML approaches to identify archaeological features in high-resolution satellite imagery (or other remotely sensed data sources). We seek to balance the disproportionately optimistic literature related to the application of ML to archaeological prospection through a discussion of limitations, challenges and other difficulties. We further seek to raise awareness among researchers of the time, effort, expertise and resources necessary to implement ML successfully, so that they can make an informed choice between ML and manual inspection approaches.

Automated object detection has been the holy grail of archaeological remote sensing for the last two decades. Machine learning (ML) models have proven able to detect uniform features across a consistent background, but more variegated imagery remains a challenge. We set out to detect burial mounds in satellite imagery from a diverse landscape in Central Bulgaria using a pre-trained Convolutional Neural Network (CNN) plus additional but low-touch training to improve performance. Training was accomplished using MOUND/NOT MOUND cutouts, and the model assessed arbitrary tiles of the same size from the image. Results were assessed using field data.

Validation of results against field data showed that self-reported success rates were misleadingly high, and that the model was misidentifying most features. Setting an identification threshold at 60% probability, and noting that we used an approach where the CNN assessed tiles of a fixed size, tile-based false negative rates were 95–96%, false positive rates were 87–95% of tagged tiles, while true positives were only 5–13%. Counterintuitively, the model provided with training data selected for highly visible mounds (rather than all mounds) performed worse. Development of the model, meanwhile, required approximately 135 person-hours of work.

Our attempt to deploy a pre-trained CNN demonstrates the limitations of this approach when it is used to detect varied features of different sizes within a heterogeneous landscape that contains confounding natural and modern features, such as roads, forests and field boundaries. The model has detected incidental features rather than the mounds themselves, making external validation with field data an essential part of CNN workflows. Correcting the model would require refining the training data as well as adopting different approaches to model choice and execution, raising the computational requirements beyond the level of most cultural heritage practitioners.

Improving the pre-trained model’s performance would require considerable time and resources, on top of the time already invested. The degree of manual intervention required – particularly around the subsetting and annotation of training data – is so significant that it raises the question of whether it would be more efficient to identify all of the mounds manually, either through brute-force inspection by experts or by crowdsourcing the analysis to trained – or even untrained – volunteers. Researchers and heritage specialists seeking efficient methods for extracting features from remotely sensed data should weigh the costs and benefits of ML versus manual approaches carefully.

Our literature review indicates that use of artificial intelligence (AI) and ML approaches to archaeological prospection have grown exponentially in the past decade, approaching adoption levels associated with “crossing the chasm” from innovators and early adopters to the majority of researchers. The literature itself, however, is overwhelmingly positive, reflecting some combination of publication bias and a rhetoric of unconditional success. This paper presents the failure of a good-faith attempt to utilise these approaches as a counterbalance and cautionary tale to potential adopters of the technology. Early-majority adopters may find ML difficult to implement effectively in real-life scenarios.

Unlike many high-profile reports from well-funded projects, our paper represents a serious but modestly resourced attempt to apply an ML approach to archaeological remote sensing, using techniques like transfer learning that are promoted as solutions to time and cost problems associated with, e.g. annotating and manipulating training data. While the majority of articles uncritically promote ML, or only discuss how challenges were overcome, our paper investigates how – despite reasonable self-reported scores – the model failed to locate the target features when compared to field data. We also present time, expertise and resourcing requirements, a rarity in ML-for-archaeology publications.

This study aims to describe key elements that are critical to virtual qualitative research especially while working with practitioners as participants.

This paper takes a reflexive researcher approach using a case study to explore how researchers adopted a qualitative research approach using digital technology. We use five principles suggested by Boland et al. (2022) as a framework to consider and reflect on our experiences as researchers and those of our participants.

We highlight the gatekeeper’s support, trusted relationship with the organisations, interpersonal skills of interviewers, stringent measures of securing data and shared experiences of interviewee and interviewers helped complete virtual research. We recommend that four key factors such as digital competency, feasibility, flexibility and resilience should be considered while undertaking or commissioning virtual, qualitative research studies.

Social care practitioners and qualitative researchers increasingly negotiate with digital technologies to undertake their work. In this paper, we evidence how online qualitative approaches can be effective provided challenges are dealt with diligently in each stage of the research process.

Our study aims to evaluate the impact of infrastructure and public investment on private investment in machinery and equipment in Brazil from 1947 to 2017. The contribution of our article to the existing literature lies in providing a more comprehensive understanding of the presence or absence of the crowding effect in the Brazilian economy by leveraging an extensive historical database. Our central argument posits that the recent decline in private capital accumulation over the last few decades can be attributed to shifts in economic policies – moving from a developmentalist orientation to nondevelopmental guidance since the early 1990s, which is reflected in the diminished levels of public investment and infrastructure since the 1980s.

We conducted a series of econometric regressions utilizing the autoregressive distributed lag (ARDL) model as our chosen econometric methodology.

Employing two different variables to measure public investment and infrastructure, our results – robust across various specifications – have substantiated the existence of a crowding-in effect in Brazil over the examined period. Thus, we have empirical evidence indicating that the state has influenced private capital accumulation in the Brazilian economy over the past decades.

Our article contributes to the existing literature by offering a more comprehensive understanding of the crowding effect in the Brazilian economy, utilizing an extensive historical database.

This study aims to develop an entrepreneurial business model capable of addressing and preventing the exploitation and inequality that traditionally have resulted from entrepreneurship, particularly in emerging economies.

The research uses systems thinking, the first law of cybernetics, and the principles of harmony to formulate a systemic solution to the problem, which it exemplifies via six purposefully selected short cases drawn from diverse industry sectors and economies.

This paper demonstrates how the conventional model of entrepreneurship, often associated with colonial exploitation and resultant inequalities, can be transformed into a triple bottom line model—harmonious entrepreneurship – that integrates the traditional economic, eco-, humane, and social approaches and creates a synergy where profit, planet, and people are in harmony. The model challenges the profit maximisation/shareholder value doctrine of business success.

Only six cases are presented here, and there is a need for further research in different political-economic contexts and industry sectors. Also, the way entrepreneurship is taught needs to change so that it addresses the sustainability challenge in general and the problem of inequality in particular.

There needs to be a change in the entrepreneurial mindset and the way entrepreneurship is taught and potential entrepreneurs are trained if entrepreneurship is to address the sustainability challenge in general and the problem of inequality in particular.

This is a novel approach to the study of entrepreneurship and its impact on inequality that shows how it can ameliorate and/or prevent inequality, particularly in emerging economies, by adopting a more holistic approach to business success and supplanting “having and needing” with “being and caring”.

The purpose of this paper is to investigate the impact of the COVID-19 pandemic on company innovation, specifically centering on the quantity and quality of innovation. The paper aims to provide a comprehensive understanding of whether the epidemic inhibits innovation and the role of digital transformation in mitigating this negative impact.

The paper uses a quasi-experimental study of the COVID-19 pandemic and constructs a differential model to analyze the relationship between the epidemic and firm innovation in three dimensions: total, quantity and quality. The paper also uses a difference-in-difference-in-differences model to test whether digital transformation of firms mitigates the negative impact of the epidemic and its mechanism of action.

The results show that COVID-19 significantly reduced the overall level of firm innovation, primarily in terms of quantity rather than quality. Furthermore, this study finds that digital transformation plays a pivotal role in mitigating the pandemic’s adverse impact on innovation. By addressing financing constraints and countering demand insufficiency, digital transformation acts as a catalyst for preserving and fostering innovation during and after the pandemic.

This study extends the current research on the pandemic’s impact on firm innovation at the micro level. It offers valuable insights into strategies for fostering digital transformation among Chinese enterprises in the post-pandemic era.

In international business (IB), the discussion of COVID-19-related global value chain (GVC) models driving resilience has taken momentum since May 2020. The purpose of this study is to uncover insights that the pandemic provided as a unique research opportunity, holistically, revealing the significant role of non-lead firms in GVC outcomes and resilience. This allows to extend theory as the authors critically identify impact criteria and assess interdependence and valence, thus progressing the traditional (pre-pandemic) IB view of GVC governance and orchestration.

This study opts for an integrative review to help create a much-needed extension of IB theory by means of a critical perspective on GVC theory. The authors examine the extant body of IB literature as the relevant stock of collective IB knowledge prompted by the COVID-19 pandemic, uncovering contributions – with a focus on the role of non-lead firms in orchestration and resilience – that allows to clarify what was not evident pre-pandemic. With this, the authors move the theory from its efficiency focus to a better recognition of the interdependencies of power and profit outcomes stemming from asymmetries of interrelationships. By design, the authors focus on the unique research period of the pandemic and orchestration complexities along the development of configurational arguments beyond simple correlations (Fiss, 2011), revealing key dependencies as key themes. The authors highlight further research avenues following Snyder (2019) that are called upon to strengthen that understanding and that helps extend theory.

This research provides a critical perspective on the application of the traditional IB views for GVC governance (designed for efficiency, cost and proximity to markets with pre-dominance for just in time), which has shifted during the pandemic to accommodate for adaptation and adjustment to resilience and just in case considerations. The holistic review reveals not only the key country- and multinational enterprise (MNE)-dependencies with residual impact determining the balance between just-in-time and just-in-case. Also, the authors advance the understanding of the (un)balance of the traditional GVC – focused on just-in-case rather than just-in-time through a lead and non-lead GVC participation and power lens yet rarely observed. The authors find that governance should not be construed as “management” such that it resolves into decisions undertaken in lead firms for execution in subordinate GVC participants. Autonomy allows to subsidiary units by MNE lead firms and/or exercised by (mainly, innovative) non-subsidiary GVC participant firms, is uncovered as a key driver in this. Greater delegation capacity appears to help provide resilience to loss in profit, with a recognition that there may be a dynamic trade-off between power and profit. In addition, the authors are able to identify correlations with innovation, demand elasticity, digital uptake, investment and other, that the authors trust will set the scene for additional research deepening and extending the findings.

Integrative literature reviews include a problem formulation (i.e. that is limited to published topics around an emerging theme) and are hence very focused in nature and approach. This applies to this paper. Data analysis in this method is not typically using statistical methods in contrast to meta-analyses. Also, the authors limit the sample to a relatively short time period with 33 publications analysed, purposefully focusing on the most prompt and “acute” insights into GVCs during the pandemic.

The traditional GVC governance model is designed for efficiency, cost and proximity to markets with pre-dominance for just in time. The authors reveal dependencies that are instrumental to better understand lead and non-lead interaction and relative autonomy, with a focus on residual impact determining the balance between just-in-time and just-in-case that, if in the sought equilibrium and agile, can allow alignment with context and this resilience. This paper specifically provides practical insights and visualization that highlights stages/“ripple” effects and their impact and the questions to ask as stakeholders look for GVC resilience. This includes, int.al., firms and their role as strategic agents, prompting participants through the learnings from exogenous shock to realign their strategies, redistributed manufacturing of production across subsidiary and non-subsidiary non-lead firms, greater competition and hence power for suppliers leveraging resilience and innovation, greater understanding of localization and regionalization of production of essential supplies, interaction with governments, and of investment impacts abroad especially to secure GVC participation.

The insights provided through this extension of theory with its literature review reveal the importance of aligning IB research into GVCs to factors that became visible through alternative or unusual settings, as they have the power to reveal the limitations of traditional views. In this case, a mainly efficiency-led, just-in-time focused GVC governance model is reviewed through the literature that emanated during the pandemic, with a critical perspective, which helped uncover and underline the complexities and evolution of GVC governance, providing fundamental support to solutioning the continuing global supply chain challenges that started as a result of the pandemic and are yet again accelerated by the Ukraine and Middle Eastern wars and its impact with, int.al., concerns over possible severe global food, labour/migration and resources crises. IB holds a social responsibility to help identify critical challenges from the disciplinary perspective and help advance resilience for social benefit.

This paper supports the original IB theory development by extending GVC theory into the lead – non-lead dynamics that may, under certain conditions, provide a “Resilience wall” for GVCs. The value created through insights stemming from a unique period of time for GVC is significant. It allows us thus also to pave the way to an emerging and critical research adaption looking into equilibrium, nuancing demand elasticity, better understanding trade and investment impacts along GVCs and more. By examining views on the sources of pandemic risks in a possibly unique setting, the authors offer added value from extant IB research insights by combining them, revealing the importance for GVCs to investigate not only key dependencies between the exogenous shock, i.e. context, and the impacts assessed through this literature but to further use their inherent value to create a framework for further conceptualization and extension of the traditional IB view on GVC governance. This work illustrates the urgency and importance for IB to take a timely and possibly more critical approach to the investigation of governance models that have, to date, shown some significant limitations.