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This article examines the relationship between financial risk management and succession planning in family businesses. Motivated by the Theory of Planned Behaviour, we hypothesize that the use of professional risk management practices is associated with an increased likelihood that businesses adopt professionalized approaches to succession planning. We then investigate if succession planning professionalization is, in turn, positively related to the financial performance of family businesses.

We apply binary probit and ordered dependent variable regressions to unique data generated from a survey sample of Australian family businesses. To check the robustness of our results to potential endogeneity concerns we apply difference tests to propensity score matched sub-samples from our original cohort of respondents.

The results show that, in contrast to verbal or absent succession arrangements, formal written succession plans are both positively associated with the use of financial risk management practices and with superior financial performance in family businesses.

Our arguments and findings suggest that active financial risk management provides a platform for planning succession in family businesses, and that this links with improved short-term financial performance. In light of the critical role that succession plays in ensuring long-term business sustainability, our findings provide important and novel insights into the conditions under which family businesses are most likely to use formal professionalized succession planning.

The purpose of this paper is to introduce the concept of gathering places in disaster recovery, and describe types of active gathering places where residents and aid workers in Southern Texas, USA, came seeking resources, information and emotional support one month after Hurricane Harvey.

Semi-structured interviews in the field with 81 residents and 44 aid workers identified active gathering places and their functions. Researchers utilized a snowball sample design to identify and visit further gathering places until saturation. Field observations and a regional damage survey conducted by car add further context to interview data.

In total, 22 distinct types of gathering places were identified from the 123 unique gathering places documented. Overall, the displacement of residents created an obstacle to their recovery and access to resources and gathering places; residents characterized a lack of formalized emotional support centers – primarily relying on informal gatherings with friends and neighbors to meet their needs; and gathering places were limited in their ability to foster a communal recovery among the residents.

This study addresses a gap in the research, focusing on where and how individuals access resources, information and emotional support in the short-term recovery following a disaster event. This research combines two traditions, hazards geography and disaster sociology, to investigate what gathering places exist one month after a major disaster, where those places are located, and what purpose they serve.

The purpose of the research is to gain an understanding about how stock market investors impact various behavioural personality traits in various consumer groups with differing levels of motivation and capacity to absorb emerging stock market data.

The research has used structural equation modelling (SEM) to test the validity of the theoretical model.

The current paper is the first study that uses stock market data from an emerging economy to examine the relationship between stock market investment and different behavioural patterns such as stock market attachment, trust, satisfaction and loyalty. The authors observe the presence of direct positive relationships between stock market investment and different behavioural personality traits. Moreover, the authors also observe that stock market attachment can be seen as an intermediary variable between stock investment involvement and satisfaction. The empirical findings also suggest the presence of indirect relationships between stock investment involvement and satisfaction and between stock market attachment and loyalty. The authors find that the indirect relationship between stock market attachment and loyalty occurs when the level of satisfaction is higher. Therefore, satisfaction appears to facilitate the relationship between stock market attachment and loyalty.

One major limitation of the study is data availability. More specifically, the study was conducted with customers of eight different banks in the province of Eskisehir, Turkey. From the 250 questionnaires distributed, 173 were returned, yielding a response rate of 69.2%.

By identifying the trait characteristics of segments of stock market participants relative to their propensity to invest in stocks, it is possible to tailor messages that influence people to invest for the long term.

The paper deploys stock market data from an emerging economy to investigate the relationship between stock market investment and different surface traits such as stock market attachment, trust, satisfaction and loyalty. To the best of the authors' knowledge the current paper is the first such study.

This study aims to develop a hierarchical model that uncovers the relationships between challenges confronting Africa's organ transplant supply chain systems.

Eleven challenges (variables) were identified after a comprehensive review of the existing literature. The contextual interactions among these variables were analysed from the perspectives of health-care stakeholders in two sub-Saharan Africa (SSA) countries (Nigeria and Uganda), using Delphi-interpretive structural modelling-cross-impact matrix multiplication applied to classification (MICMAC) techniques.

The findings reveal that weak regulatory frameworks, insufficient information systems and a lack of necessary skills make it challenging for critical actors to perform the tasks effectively. The interaction effects of these challenges weaken organ supply chains and make it less efficient, giving rise to negative externalities such as black markets for donated organs and organ tourism/trafficking.

This paper establishes a solid foundation for a critical topic that could significantly impact human health and life once the government or non-profit ecosystem matures. The MICMAC analysis in this paper provides a methodological approach for future studies wishing to further develop the organ supply chain structural models.

The study provides valuable insights for experts and policymakers on where to prioritise efforts in designing interventions to strengthen organ transplantation supply chains in developing countries.

This study is one of the first to empirically examine the challenges of organ transplant supply chains from an SSA perspective, including theoretically grounded explanations from data collected in two developing countries.

This study aims to develop a theoretical framework that marketing practitioners and scholars can adopt to enhance their understanding of how firms can effectively deploy and use digital human avatars as part of their global digital marketing strategy. By doing so, we inform investors of ongoing digital transformations of marketing practices that will equip marketeers to provide scalable, tailored, reliable and relevant digital self-service interactions to users, consequently improving the user/customer experience.

Thematic analysis was used to discover factors to enable the successful implementation of digital human avatars, drawing on in-depth interviews with fourteen executives of digital human avatars developer companies worldwide and analysis of ten podcasts and webinars with artificial intelligence (AI) experts.

Digital human avatars revitalise the international dynamic marketing capabilities (IDMCs) of firms by integrating advanced technologies that transform user interactions, improve engagement and facilitate knowledge acquisition, dissemination and usage across various sectors and business units globally. This integration promotes a dynamic approach to international brands, customer relationships and marketing knowledge management capabilities, offering profound value to users and firms.

Our first limitation is a lack of diversity in data sources. As digital human avatars are an emerging field, we had to limit our study to 14 experts in AI and 10 podcasts. While this method provides deep insights into the perspectives of those directly involved in the development and implementation of digital human avatars, it may not capture the views of end-users or consumers who interact with these avatars, which can be an avenue for further research. Our second limitation is the potential bias in the interpretation of our interview data and podcasts. This study’s approach to data analysis, where themes are derived from the data itself, carries a risk of subjective interpretation by the researchers. Future studies are encouraged to investigate the impact of digital human avatars across different organisational contexts and ecosystems, especially focusing on how these technologies are integrated and perceived in various international markets.

The novel framework has direct implications for innovators and marketing practitioners who aim to adopt digital human avatars in their marketing practices to enhance the effectiveness of international marketing strategies.

The adoption of digital human avatars can alleviate loneliest elderly and vulnerable people by being a companion. The human-like characteristics can impact sense of presence and attachment.

The novelty of our study lies in exploring the characteristics of technologies and practical factors that maximise the successful adoption of digital human avatars. We advance and contribute to the emerging theory of avatar marketing, IDMCs and absorptive capacity by demonstrating how digital human avatars could be adopted as part of a firm’s global digital marketing strategy. We focus specifically on six dimensions: outcomes and benefits, enhancements and capabilities, applications and domains, future implications, foundational elements and challenges and considerations. This framework has direct implications for innovators and marketing practitioners who aim to adopt digital human avatars in their marketing practices to enhance the effectiveness of international marketing strategies.

Peace engineering and compassionate operations can unlock the potential of emerging technologies for social good. This work aims to investigate the integration of peace engineering and compassionate operations by proposing an integrative framework and identifying the main drivers regarding social good, considering the Sustainable Development Goals (SDGs) landscape.

The authors used a two-stage methodology by employing a narrative literature review in the first stage to identify the relationships and drivers and propose an original framework. In the second stage, the authors utilized an expert panel to validate the framework’s drivers.

The authors identified five main categories related to peace engineering and compassionate operations, which were then used to support the categorization of the drivers. In the second stage, the authors validated the drivers with a panel of academicians and experienced industry practitioners.

The proposed framework can provide insightful directions for practitioners and governments to develop strategies and projects in different contexts, including humanitarian logistics, climate change crises, supply chain disruptions, etc.

This work makes unique contributions by reinvigorating an amalgamation of the peace engineering and compassionate operations arenas and their integration with the SDGs to enable enhanced social good, supported by cutting-edge technologies. Thus, this framework’s contributions encompass essential theoretical, managerial, and social implications.

The feasibility of process mining combined with simulation techniques in estimating the effectiveness of COVID-19 prevention strategies on infection and mortality trends to determine best practices is assessed in this study. The quarantine event log is built from the CUSP (the COVID-19 US State Policy) database, where the dates of implemented social policies in the USA to respond to the COVID-19 pandemic are documented.

COVID-19 is a highly infectious disease leading to a very high death toll worldwide. In most countries, the governments have resorted to a series of drastic strategies to prevent the outbreak by restricting the activities and movement among their population for a predefined time. Heretofore, different approaches have been published to estimate quarantine strategies and the majority signify the positive effect on managing this pandemic. Notably, the process perspective of COVID-19 datasets is of less concern among researchers. The purpose of this paper is to exploit the process mining techniques to model and analyze the quarantine implementation processes.

The discovered process model has 51 process variants for 51 cases (states), which indicate the quarantine activities were executed in different orders and periods during the pandemic. The time interval analysis between activities reveals the states with the most extended quarantine periods. These primary process mining insights are applied to define scenarios and variables of an agent-based model. The simulation findings indicate a meaningful relation between enforcing quarantine strategies and a declining trend of infection by 90% in the case of following strict quarantine and mask mandates. It is observed that in the post-quarantine period, the disease repeats its ascending trend unless implementation of different intervention strategies likes vaccination.

This study is the first in introducing process mining techniques in analyzing the COVID-19 quarantine strategies impact. The findings provide valuable insights for policymakers to proper control strategies and the process mining research community in expanding more process-related analysis on this pandemic. Also, the results have broad implications for research in other fields like information science to estimate the impact of quarantine strategies on process patterns in library systems.

The purpose of this paper is to identify the effect of radical innovation and incremental innovation on the competitive advantage of Jordanian industrial companies and identify the moderating role of technological intensity.

For this study’s purposes, 303 questionnaires from employees of 30 manufacturing firms were analysed. Convergent validity and discriminant validity tests were performed through structural equation modelling in the Smart-PLS programme. Data reliability was confirmed. A bootstrapping technique was used to analyse the data. Multi-group analysis was performed to investigate the moderating role of technological intensity.

Empirical results showed that both radical innovation and incremental innovation explain 60.2% of the variance in competitive advantage and that both constructs have a statistically significant effect on competitive advantage. The results also revealed that the relationship between radical innovation and competitive advantage is modified through the high-tech industries. Meanwhile, the relationship between incremental innovation and competitive advantage is modified through the low-tech industries.

This cross-sectional study provides a snapshot at a given moment in time, a methodological limitation that affects the generalization of its results and the results are limited to one country, Jordan.

This study promotes the idea of focusing on radical and incremental innovation to enhance competitive advantage in the Jordanian manufacturing sector and knowing the effect of technological intensity in this relationship.

This study has important implications for leaders in the Jordanian manufacturing sector in general, as the study highlights the importance of radical innovation and incremental innovation to enhance the competitive advantage, especially in light of the technological intensity in this sector, and thus, increase the innovative capabilities of this firms, which leads to an increase in the level of competitive advantage.

This study aims to investigate the perspective of corporate philanthropy during the coronavirus disease 2019 (COVID-19) in China for firms with various levels of corporate social responsibility (CSR). Specifically, the study appraises the impact of the COVID-19 pandemic on the stock returns and sustainable development of Chinese-listed companies and determines the likelihood of paying donations vis-à-vis firm reputation.

The study used data from 117 Chinese-listed firms engaged in philanthropy during the COVID-19 pandemic. The authors also utilized the stock returns and cash donation data, and owing to the cross-sectional data and continuous nature of dependent variables, they employed the ordinary least squares regression to test the research hypotheses.

The results show that irresponsible actions have a positive relationship with donations. The study particularly reveals that irresponsible firms have significant negative abnormal returns during the first wave of the COVID-19 pandemic.

To the best of our knowledge, this is the first empirical study to explore the perspective of corporate philanthropy during the COVID-19 pandemic for companies with different CSR levels. This study contributes to the empirical research on CSR and provides insights for managerial-cum-financial decisions to encourage managers of irresponsible firms to pursue philanthropic behaviors after crisis events.