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This paper aims to provide a maturity model for information security awareness (MMISA), based on the literature, expert interviews and feedback. In addition to developing the MMISA, the authors investigate the role of the three decisive factors that affect ISA maturity level: risk management mechanism, organizational structure and ISA.

The research methodology is a combined one; qualitative and quantitative methods were applied, including surveying the literature, interviews and developing a survey to collect quantitative data about decisive factors that affect ISA maturity level. The authors perform a variance-based partial least squares-structural equation modeling (PLS-SEM) investigation of the relationships between these factors.

The investigation of decisive factors of ISA maturity levels revealed that if the authors identify a strong risk assessment mechanism (through a documented methodology and reliable results), the authors can expect a high level of ISA. If there is a well-defined organizational structure with clear responsibilities, this supports the linking of a risk management mechanism with the level of ISA. The connection between organizational structure and ISA maturity level is supported by ISA activities: an increased level of awareness actions strengthens an organizational structure via the best practices learned by the staff.

The main contribution of the proposed MMISA model is that the model offers controls and audit evidence for maturity levels. Beyond that, the authors distinguish in the MMISA model controls supporting knowledge and controls supporting attitude, emphasizing that this is not enough to know what to do, but the proper attitude is required too. The authors didn't find any other ISA maturity model which has a similar feature. The contribution of the authors' work is that the authors provide a method for solving this complex measurement problem via the MMISA, which also offers direct guidance for the daily practices of organizations.

Global crises have become increasingly recurrent events that jeopardize public-private partnerships (PPPs). In this context, the purpose of this paper is to expose the PPP-crisis research agenda by combining bibliometric and network analyses.

The PPP literature associated with global crises between the 2008 global financial crisis and 2022 was analyzed in three stages: (1) paper selection and screening for the inclusion/exclusion of articles relevant to this research, (2) semantic network development for examining thematic relationships among selected papers by considering the co-occurrence of keywords within the chosen studies and (3) calculation of network metrics for analysis.

The paper identified six research avenues for the PPP-crisis agenda: public interest, relational governance, risk management, user-pay PPPs, crisis management and financial performance. The PPP-crisis literature has spread significantly in the last five years driven by the case study approaches on a national or regional basis. Conversely, non-crisis periods generate room to strengthen user-pay PPPs and relational governance. The pandemic and post-pandemic times shared the priorities of the 2008 financial crisis but also strengthened the management of the risks and the structural drivers of the global crisis.

This study demonstrates that during global crisis periods, the public interest and financial performance gain relevance in a detriment of structural solutions to social legitimacy erosion of PPPs because of the urgency of giving tools to the public and private sectors to tackle the financial issues, which steer future issues for PPPs.

The substantial expansion of technology and the efficacy of digital platforms in reaching young audiences have led to enhanced targeting and customization of promotional communications. Notwithstanding the expansion and efficacy of contemporary advertising platforms, scholarly attention has not kept pace with this domain of inquiry. This study aims to assess the antecedents of Google Shopping Ads (GSA) on intention to purchase behavior among the Generation Y and Z cohorts.

The current study used a quantitative approach and snowball sampling technique to gather primary data via a questionnaire and Google Forms, which resulted in the collection of 5,808 questionnaires among the cohort members. A principal component analysis and multigroup confirmatory multigroup structural equation modeling (between Generation Y and Z) were used to assess the research data and model.

The results show positive trust and perceived value associations with intention to purchase, particularly among Generation Y and Z consumers. The findings also show negative irritation, product risk and time risk associations with intention to purchase, especially among the Generation Y cohort, which indicates that young consumers generally do not observe perceived risk due to the usage of GSA.

GSA will continue to grow and become an increasingly important integrated marketing communications tool as the digital landscape develops. It can be concluded that young consumers show a high degree of perceived value and low levels of perceived risk due to the use of GSA. This study, therefore, promotes improved understanding among academics, marketers and businesses of search engine advertising among young cohorts of consumers (Generation Y and Z) in a developing country context.

Unforeseen events can disrupt the operational process and negatively impact emergency resources optimization and its supply chain. A limited number of studies have addressed risk management issues in the context of emergency supply chains, and this existing research lacks inbuilt and practical techniques that can significantly affect the reliability of risk management outcomes. Therefore, this paper aims to identify and practically analyze the specific risk factors that can most likely disrupt the normal functioning of the emergency supply chain in disaster relief operations.

This paper has used a three-step process to investigate and evaluate risk factors associated with the emergency supply chain. First, the study conducts a comprehensive literature review to identify the risk factors. Second, the research develops a questionnaire survey to validate and classify the identified risk factors. At the end of this step, the study develops a hierarchical structure. Finally, the research investigates the weighted priority of the validated risk factors using the fuzzy-analytical hierarchy process (FAHP) methodology. Experts were required to provide subjective judgments.

This paper identified and validated 28 specific risk factors prevalent in emergency supply chains. Based on their contextual meanings, the research classified these risk factors into two main categories: internal and external risk factors; four subcategories: demand, supply, infrastructural and environmental risk factors; and 11 risk types: forecast, inventory, procurement, supplier, quality, transportation, warehousing, systems, disruption, social and political risk factors. The most significant risk factors include war and terrorism, the absence of legislative rules that can influence and support disaster relief operations, the impact of cascading disasters, limited quality of relief supplies and sanctions and constraints that can hinder stakeholder collaboration. Therefore, emergency supply chain managers should adopt appropriate strategies to mitigate these risk factors.

This study will contribute to the general knowledge of risk management in emergency supply chains. The identified risk factors and structural hierarchy taxonomic diagram will provide a comprehensive risk database for emergency supply chains.

The research findings will provide comprehensive and systemic support for respective practitioners and policymakers to obtain a firm understanding of the different risk categories and specific risk factors that can impede the effective functioning of the emergency supply chain during immediate disaster relief operations. Therefore, this will inform the need for the improvement of practices in critical aspects of the emergency supply chain through the selection of logistics and supply chain strategies that can ensure the robustness and resilience of the system.

This research uses empirical data to identify, categorize and validate risk factors in emergency supply chains. This study contributes to the theory of supply chain risk management. The study also adopts the fuzzy-AHP technique to evaluate and prioritize these risk factors to inform practitioners and policymakers of the most significant risk factors. Furthermore, this study serves as the first phase of managing risk in emergency supply chains since it motivates future studies to empirically identify, evaluate and select effective strategies that can eliminate or minimize the effects of these risk factors.

Financial stability has become a focal point for central banks since the global financial crisis. However, the optimal mix between monetary and financial stability policies remains unclear. In this study, the “soft” approach to such policy mix was tested – how often monetary policy (in inflation reports) analyses financial stability issues. This paper aims to discuss the aforementioned objective.

A total of 648 inflation reports published by 11 central banks from post-communist countries in 1998-2019 were reviewed using a text-mining method.

Results show that financial stability topics (mainly cyclical aspects of systemic risk) on average account for only 2%of inflation reports’ content. Although this share has grown somewhat since the global financial crisis (in CZ, HU and PL), it still remains at a low level. Thus, not enough evidence was found on the use of a “soft” policy mix in post-communist countries.

Given the strong interactions between price and financial stability, this paper emphasizes the need to increase the attention of monetary policymakers to financial stability issues.

The study combines two research areas, i.e. monetary policy and modern text mining techniques on a sample of post-communist countries, something which to the best of the authors’ knowledge has not been sufficiently explored in the literature before.

The smoothness of the high-speed railway (HSR) on the bridge may exceed the allowable standard when an earthquake causes vibrations for HSR bridges, which may threaten the safety of running trains. Indeed, few studies have evaluated the exceeding probability of rail displacement exceeding the allowable standard. The purposes of this article are to provide a method for investigating the exceeding probability of the rail displacement of HSRs under seismic excitation and to calculate the exceeding probability.

In order to investigate the exceeding probability of the rail displacement under different seismic excitations, the workflow of analyzing the smoothness of the rail based on incremental dynamic analysis (IDA) is proposed, and the intensity measure and limit state for the exceeding probability analysis of HSRs are defined. Then a finite element model (FEM) of an assumed HSR track-bridge system is constructed, which comprises a five-span simply-supported girder bridge supporting a finite length CRTS II ballastless track. Under different seismic excitations, the seismic displacement response of the rail is calculated; the character of the rail displacement is analyzed; and the exceeding probability of the rail vertical displacement exceeding the allowable standard (2mm) is investigated.

The results show that: (1) The bridge-abutment joint position may form a step-like under seismic excitation, threatening the running safety of high-speed trains under seismic excitations, and the rail displacements at mid-span positions are bigger than that at other positions on the bridge. (2) The exceeding probability of rail displacement is up to about 44% when PGA = 0.01g, which is the level-five risk probability and can be described as 'very likely to happen'. (3) The exceeding probability of the rail at the mid-span positions is bigger than that above other positions of the bridge, and the mid-span positions of the track-bridge system above the bridge may be the most hazardous area for the running safety of trains under seismic excitation when high-speed trains run on bridges.

The work extends the seismic hazardous analysis of HSRs and would lead to a better understanding of the exceeding probability for the rail of HSRs under seismic excitations and better references for the alert of the HSR operation.

The purpose of this study is to examine how different innovation efforts can support multinational enterprises’ (MNEs’) pursuits of sustainable development goals (SDGs) in emerging markets and under what circumstances they are applied.

The article comprises in-depth case studies on two high-profile Swedish MNEs: a telecom firm and a fast-fashion firm, with data collected both at the headquarter-level and local-market level.

The study shows that MNEs pursue a selection of prioritized SDGs in emerging markets. To overcome challenges related to attaining these goals, we find that MNEs engage in innovation efforts at different levels of commitment. In some instances, they engage in operational innovation aimed at relieving symptoms of sustainability misconduct and ensuring compliance. In other instances, they engage in systemic innovation efforts, which involve the actual market structures underlying sustainability problems.

MNEs are increasingly incorporating the United Nations SDGs into their innovation strategies. The study contributes to international business research on MNEs’ roles in realizing the SDGs by conceptualizing and discussing two pertinent approaches to innovation.