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Different age groups display different shopping patterns in terms of how and where consumers buy products. During times of crisis, such behavioural differences become even more striking yet remain under-researched with respect to elderly consumers. This paper investigates the impact of age on retail-related behavioural changes and behavioural stability of elderly shoppers (in comparison to younger consumers) during a crisis.

The authors surveyed 643 Austrian consumers to assess the impact of perceived threat on behavioural change and the moderating effect of age groups. Based on findings from this survey, they subsequently conducted 51 semi-structured interviews to understand the causes of behavioural change and behavioural stability during a crisis.

Elderly shoppers display more stable shopping behaviour during a crisis compared to younger consumers, which is influenced by perceived threat related to the crisis. Such findings indicate that elderly shoppers reinforce their learnt and embedded shopping patterns. The causes of change and stability in behaviour include environmental and inter-personal factors.

Through the lens of social cognitive theory, protection motivation theory and dual process theory, this research contributes to an improved understanding of changes in shopping behaviour of elderly consumers, its antecedents and consequences during a time of crisis. The authors reveal reasons that lead to behavioural stability, hence the absence of change, in terms of shopping during a crisis. They further outline implications for retailers that might wish to better respond to shopping behaviours of the elderly.

This study systematically explores the patterns and connections in the behavioural bias and investment decisions of the existing literature in the Scopus database published between 2007 and 2022. The purpose of this paper is to address this issue.

In the article it was determined which contributed documents were the most significant in this particular subject area along with the citations, publications and nations that were associated with them. The bibliographic coupling offered more in-depth insights into the papers by organizing them into distinct groups. The pattern of the publications has been brought to light, and the connection between different types of literature has provided insight into the path that future studies should take.

This study considered only articles from the Scopus database. Future studies can be based on papers that have been published in other databases.

The outcome of this study provides valuable insights into the intellectual structure and biases of investors and adds value to existing knowledge. This review provides a road map for the future trend of research on behavioural bias and investment decisions.

The world-over, it is evident that, numbers and frequency of natural disasters have increased tremendously. The effects have given birth to a worldwide, all-inclusive humanitarian response and preparedness. In Zimbabwe, Cyclone Idai has ushered in the exploitation of various social media platforms by humanitarian organisations as a way of reaching out to the wider population on critical issues pertaining to the devastating effects of the cyclone. This study herein, aims to interrogate the efficacy of various social media platforms that were exploited by various humanitarian organisation involved in the Cyclone Idai humanitarian response. The various social media platforms are interrogated to establish their contribution to inclusivity or lack of it in relaying humanitarian interventions.

A mixed-method approach was used to conduct the research. Quantitative and qualitative methods were applied to gather the data. Quantitative data was collected using questionnaires with Likert scales and other closed questions provided. These were administered to representatives from the government, United Nations, donors, non-governmental organisations (NGOs), and members of the community. On the contrary, qualitative data was gathered from members of the community and humanitarian organisations through open-ended responses provided from interviews. Quantitative data was collected from a total of 384 stakeholder representatives who were randomly selected from Chimanimani district of Manicaland province. In addition, 12 interview participants were purposively selected to complement the research tools listed above.

The study findings show that social media platforms to a greater extent are effective tools for creating inclusive humanitarian response. The study findings reveal that social media has a significant positive influence on inclusive humanitarian response, with a 5% level of significance. These quantitative results agree with results obtained from interviewed participants. Managers of NGOs, community-based groups, government agencies and churches engaged in managing rescue, relief and humanitarian aid are supposed to access the study's findings in the future, and may find the results resourceful.

This study's generalisability to other districts and countries is constrained because it was conducted in the setting of the Chimanimani district. Future research can therefore be expanded to other Zimbabwean areas as well as to other countries in the Southern African region and beyond.

Humanitarian supply chain managers engaged in managing rescue, relief and humanitarian aid are proposed as having access to the study's findings in the future as they may find them useful.

This study contributes to the literature by providing insights that can improve information flow. This can be achieved by including different stakeholders in decision-making through the use of social media during disaster preparedness and response processes and helping them to better prepare for and respond to future disasters.

The purpose of this paper is to explore how Ontario principals make sense of difference within student populations and how this sensemaking influences how they do their work.

The paper reports on a qualitative study in Ontario, Canada that included 59 semistructured interviews with school principals from English public, secular school districts in Southern Ontario.

Four themes emerged in principals’ descriptions of student populations: perceiving everyone as the same, or homogeneous; perceiving visible differences associated with particular religions, race and cultures; perceiving invisible or less visible differences, such as academic differences, socioeconomic status, mental health issues, gender identity and sexual orientation; and perceiving both visible and less visible differences through an inclusive lens. When asked about how their understanding of difference influenced how they did their work, principals’ responses varied from not influencing their work at all to influencing practices and activities. Participants’ context – both personal and local – influenced some of the work they did in their role as school principal. Lastly, multiple sources of disconnect emerged between how principals understood difference and the practices that they engage in at their school site; between their sensemaking about difference and diversity and preparing students for the twenty-first century competencies as global citizens; and between principals’ understanding of difference and diversity and existing provincial policy.

Study insights not only contribute to an existing body of literature that examines principals’ sensemaking around difference, but also extend this line of inquiry to consider how this sensemaking influences their professional practice. These findings pose additional research questions about how to approach principal professional learning for inclusive and equitable education. For example, even though principals are contractually responsible for students in their care, why is it that their efforts toward equitable and inclusive schooling appear to be limited to the school site and not the wider community?

Study findings can be used to inform principal preparation programs and professional learning opportunities. Namely, these programs should provide the skill development required as well as the time needed for principals to reflect on their local context and beliefs, and to consider how their local context and beliefs are connected to larger societal efforts to create a more inclusive and equitable society.

School leadership is integral to creating and building more inclusive and equitable public education that improves all students’ success at school. As Ontario’s general population becomes increasingly diverse, it is imperative that principals support success for all students; this can only happen if they understand the complexity of difference within their student populations and beyond, how to address these complexities and how their own understandings and beliefs influence their leadership practices.

Although other papers have examined how principals make sense of difference and diversity in student bodies, this paper also explores how this sensemaking influences how school leaders do their work.

Firms have already begun integrating artificial intelligence (AI) as a replacement for conventional performance management systems owing to its technological superiority. This transition has sparked a growing interest in determining how employees perceive and respond to performance feedback provided by AI as opposed to human supervisors.

A 2 x 2 between-subject experimental design was employed that was manipulated into four experimental conditions: AI algorithms, AI data, highly experienced human supervisors and low-experience human supervisor conditions. A one-way ANOVA and Welch t-test were used to analyze data.

Our findings revealed that with a predefined fixed formula employed for performance feedback, employees exhibited higher levels of trust in AI algorithms, had greater performance expectations and showed stronger intentions to seek performance feedback from AI algorithms than highly experienced human supervisors. Conversely, when performance feedback was provided by human supervisors, even those with less experience, in a discretionary manner, employees' perceptions were higher compared to similar feedback provided by AI data. Moreover, additional analysis findings indicated that combined AI-human performance feedback led to higher levels of employees' perceptions compared to performance feedback solely by AI or humans.

The findings of our study advocate the incorporation of AI in performance management systems and the implementation of AI-human combined feedback approaches as a potential strategy to alleviate the negative perception of employees, thereby increasing firms' return on AI investment.

Our study represents one of the initial endeavors exploring the integration of AI in performance management systems and AI-human collaboration in providing performance feedback to employees.

Prediction is a critical task in targeted online advertising, where predictions better than random guessing can translate to real economic return. This study aims to use machine learning (ML) methods to identify individuals who respond well to certain linguistic styles/persuasion techniques based on Aristotle’s means of persuasion, rhetorical devices, cognitive theories and Cialdini’s principles, given their psychometric profile.

A total of 1,022 individuals took part in the survey; participants were asked to fill out the ten item personality measure questionnaire to capture personality traits and the dysfunctional attitude scale (DAS) to measure dysfunctional beliefs and cognitive vulnerabilities. ML classification models using participant profiling information as input were developed to predict the extent to which an individual was influenced by statements that contained different linguistic styles/persuasion techniques. Several ML algorithms were used including support vector machine, LightGBM and Auto-Sklearn to predict the effect of each technique given each individual’s profile (personality, belief system and demographic data).

The findings highlight the importance of incorporating emotion-based variables as model input in predicting the influence of textual statements with embedded persuasion techniques. Across all investigated models, the influence effect could be predicted with an accuracy ranging 53%–70%, indicating the importance of testing multiple ML algorithms in the development of a persuasive communication (PC) system. The classification ability of models was highest when predicting the response to statements using rhetorical devices and flattery persuasion techniques. Contrastingly, techniques such as authority or social proof were less predictable. Adding DAS scale features improved model performance, suggesting they may be important in modelling persuasion.

In this study, the survey was limited to English-speaking countries and largely Western society values. More work is needed to ascertain the efficacy of models for other populations, cultures and languages. Most PC efforts are targeted at groups such as users, clients, shoppers and voters with this study in the communication context of education – further research is required to explore the capability of predictive ML models in other contexts. Finally, long self-reported psychological questionnaires may not be suitable for real-world deployment and could be subject to bias, thus a simpler method needs to be devised to gather user profile data such as using a subset of the most predictive features.

The findings of this study indicate that leveraging richer profiling data in conjunction with ML approaches may assist in the development of enhanced persuasive systems. There are many applications such as online apps, digital advertising, recommendation systems, chatbots and e-commerce platforms which can benefit from integrating persuasion communication systems that tailor messaging to the individual – potentially translating into higher economic returns.

This study integrates sets of features that have heretofore not been used together in developing ML-based predictive models of PC. DAS scale data, which relate to dysfunctional beliefs and cognitive vulnerabilities, were assessed for their importance in identifying effective persuasion techniques. Additionally, the work compares a range of persuasion techniques that thus far have only been studied separately. This study also demonstrates the application of various ML methods in predicting the influence of linguistic styles/persuasion techniques within textual statements and show that a robust methodology comparing a range of ML algorithms is important in the discovery of a performant model.

Social return on investment (SROI) has received increasing attention, both academically and professionally, since it was initially developed by the Roberts Enterprise Development Fund in the USA in the mid-1990s. Based on a systematic review of the literature that highlights the potential and limitations related to the academic and professional development of the SROI model, the purpose of this study is to systematize the academic debate and contribute to the future research agenda of blended value accounting.

Relying on the preferred reporting items for systematic reviews and meta-analyses approach, this study endeavors to provide reliable academic insights into the factors driving the usage of the SROI model and its further development.

A systematic literature review produced a final data set of 284 studies. The results reveal that despite the procedural accuracy characterizing the description of the model, bias-driven methodological implications, availability of resources and sector specificities can influence the type of approach taken by scholars and practitioners.

To dispel the conceptual and practical haze, this study discusses the results found, especially regarding the potential solutions offered to overcome the SROI limitations presented, as well as offers suggestions for future research.

This study aims to fill a gap in the literature and enhance a conceptual debate on the future of accounting when it concerns a blended value proposition.

The purpose of this paper is to review cases of artificial reefs built through additive manufacturing (AM) technologies and analyse their ecological goals, fabrication process, materials, structural design features and implementation location to determine predominant parameters, environmental impacts, advantages, and limitations.

The review analysed 16 cases of artificial reefs from both temperate and tropical regions. These were categorised based on the AM process used, the mortar material used (crucial for biological applications), the structural design features and the location of implementation. These parameters are assessed to determine how effectively the designs meet the stipulated ecological goals, how AM technologies demonstrate their potential in comparison to conventional methods and the preference locations of these implementations.

The overview revealed that the dominant artificial reef implementation occurs in the Mediterranean and Atlantic Seas, both accounting for 24%. The remaining cases were in the Australian Sea (20%), the South Asia Sea (12%), the Persian Gulf and the Pacific Ocean, both with 8%, and the Indian Sea with 4% of all the cases studied. It was concluded that fused filament fabrication, binder jetting and material extrusion represent the main AM processes used to build artificial reefs. Cementitious materials, ceramics, polymers and geopolymer formulations were used, incorporating aggregates from mineral residues, biological wastes and pozzolan materials, to reduce environmental impacts, promote the circular economy and be more beneficial for marine ecosystems. The evaluation ranking assessed how well their design and materials align with their ecological goals, demonstrating that five cases were ranked with high effectiveness, ten projects with moderate effectiveness and one case with low effectiveness.

AM represents an innovative method for marine restoration and management. It offers a rapid prototyping technique for design validation and enables the creation of highly complex shapes for habitat diversification while incorporating a diverse range of materials to benefit environmental and marine species’ habitats.

This study aims to progress knowledge by developing and analyzing an integrated model of behavioral loyalty enhancement related to non-profit organization (NPO) donation. To achieve this aim, the study examines the influences of three variables of donor loyalty, namely, attitude toward beneficiaries, trust and self-esteem in one integrated model. Additionally, to compare the extent to which each variable affects donor loyalty, mediating effects are suggested.

Data from 245 Korean donors are used to investigate the proposed conceptual model using structural equation modeling with AMOS.

Findings from the study demonstrate that trust has the highest mediating influence on the intention to continue donation. Similarly, the findings reveal that self-esteem has the highest mediating influence on positive word-of-mouth (PWOM). However, the study findings suggest that attitudes toward beneficiaries are not significant predictors of both intentions to continue donating and PWOM.

The impact of trust on the intention to continue donating is more important than that of self-esteem and attitude toward the beneficiary.

Similarly, the impact of trust and self-esteem on positive WOM is more important than that of attitude toward beneficiary.

With this research, NPOs can make more budget from personal donation efficiently.

The findings of this research provide evidence that there are three important components relative to donation, namely, donor, NPO and beneficiary, and propose an integrated model which is composed of these three key components.

The purpose of this paper is to examine how exporters’ time-out periods and re-entry to various export areas impact their knowledge stock and capacity to learn from foreign markets.

This paper introduces the concept of innovation divergent export areas (IDEXAs), which refers to a group of countries with relatively similar average levels of innovation capabilities (intra-area homogeneity), and different from other areas (inter-area heterogeneity), as measured by their R&D expenditures over gross domestic product (GDP). This paper tests the hypotheses on a longitudinal sample of Spanish manufacturing companies that exported to different IDEXAs from 1990 until 2016.

The findings suggest a positive effect of IDEXA re-entry on new product and process introductions and a negative impact of a time-out period of four or more years for those export areas with higher innovation levels.

Re-internationalization offers exporters the opportunity to reuse the knowledge gained in prior exporting episodes to increase their chances of success. Hence, it is important that managers make sense of the potentially damaging exit experience, to avoid repeating the same mistakes and perform better the next time around.

This study investigates for the first time the effects of re-entry to specific export areas on exporters’ capacity to increase their innovation output. Hence, it contributes to the international business literature by examining the performance consequences of companies’ re-internationalization, a key and under-researched topic. Furthermore, most studies focus on full withdrawal from foreign markets and ignore the more common microscopic decisions concerning withdrawing from one or more export areas.