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This study aims to help understand individual donors’ preferences over different designs of humanitarian–business partnerships in managing humanitarian operations and to help understand if donors’ preferences align with their actual donation behavior.

Choice-based conjoint analysis was used to understand donation preferences for partnership designs, and a donation experiment was performed using real money to understand the alignment of donors’ preferences with actual donation behavior.

The results show that partnering with the business sector can be a valuable asset for humanitarian organizations in attracting individual donors if these partnerships are managed well in terms of partnership strategy, partnership history and partnership report and disclosure. In particular, the study finds that the donation of services and products from businesses corporations to humanitarian organizations are preferable to individual donors, rather than cash. Furthermore, donors’ preferences are not necessarily aligned with actual donation behavior.

The results highlight the importance of presenting objective data on projects to individual donors. The results also show that donors value the provision of services and products by business corporations to humanitarian operations.

Partnerships between humanitarian organizations and business corporations are important for the success of humanitarian operations. However, little is known about which partnership designs are most preferable to individual donors and have the biggest chance of being supported financially.

This article aims to investigate the role of socioeconomic factors and individual time preferences in the demand for fast-food in Russia. An individual discount rate shows the ability of a person to postpone utility from consumption to future periods.

An individual discount rate is measured through a hypothetical money experiment. The database is the special survey of the Levada analytical center conducted in 2017. Multivariate probit model enables the authors to consider the possible endogeneity of individual discount rate and reveal the relationship between socioeconomic factors and frequent fast-food consumption.

Results show that a higher individual discount rate is related to frequent consumption of fast-food. At the same time, there are factors that provoke both a higher individual discount rate and the refusal of frequent consumption of fast-food. Findings advise the prioritization of measures highlighting the short-term benefits of healthy eating and the short-term costs of avoiding it.

To the authors' knowledge, this article is the first one which presents comprehensive investigation of microeconomic factors of fast-food consumption in Russia including individual time preferences of consumers.

Brand reputation (BR) is one of the most important factors that affect the consumer–brand relationship and give businesses a competitive advantage. Businesses with a strong BR can increase their market shares and product market prices, in addition to gaining a competitive advantage. In order for businesses to have these advantages, they need to know and analyze their consumers. This study aimed to develop an alternative analysis method by using classification algorithms and regression analysis to measure and evaluate the effect of consumers' BR perceptions on their willingness to pay premium prices (WPP).

The research data were collected from 483 participants by the online survey method due to the COVID-19 pandemic. The data were first analyzed with regression analysis, and the effect of BR on WPP was found to be significant. Then, using artificial intelligence (AI) methods that were not used in previous studies, consumers' perceptions of BR and WPP were clustered and classified.

The results revealed the highest and lowest customer groups with BR and WPP and empirically demonstrated that highly accurate practical classification models can be applied to determine strategies in line with these findings.

The model proposed in this study offers an integrated approach by using AI and regression analysis together and tries to fill the gap in the literature in this field. Therefore, the novelty of this study is to quantitatively reveal and evaluate the relationship between BR and WPP by using AI classification algorithms and regression analysis together.

This study aims to conduct a bibliometric analysis on “intertemporal choice” behavior of individuals from journals in the Scopus database between 1957 and 2023. The research covered the data on the said topic since it first originated in the Scopus database and carried out performance analysis and content analysis of papers in the business management and finance disciplines.

Bibliometric analysis, including science mapping and performance analysis, followed by content analysis of the papers of identified clusters, was conducted. Three clusters based on cocitation analysis and six themes (three major and three minor) were identified using the bibliometrix package in R studio. The content analysis of the papers in these clusters and themes have been discussed in this study, along with the thematic evolution of intertemporal choice research over the period of time, paving a way for future research studies.

The review unpacks publication and citation trends of intertemporal choice behavior, the most significant authors, journals and papers along with the major clusters and themes of research based on cocitation and degree of centrality and relevance, respectively, i.e. discounting experiments and intertemporal choice, impulsivity, risk preference, time-inconsistent preference, etc.

Over the past years, the research on “intertemporal choice” has flourished because of the increasing interest of researchers and scholars from different fields and the dynamic and pervasive nature of this topic. The well-developed and scattered body of knowledge on intertemporal choice has led to the need of applying a bibliometric analysis in the intertemporal choice literature.

This paper aims to propose and evaluate an innovative approach to education for sustainable consumption (ESC) which empowers teenagers and young adults to improve sustainable consumption competences. This approach combines pedagogical learning approaches such as real-world learning (e.g. experiential learning and research-based learning) with transformative and transdisciplinary research approaches (i.e. real-world laboratory research).

Through a transdisciplinary research design, the authors explore if real-world experiments (RWEs) offer a suitable approach for sustainable consumption education at schools. RWEs are a research approach for knowledge production, aiming to go beyond temporary interventions, to establish semi-permanent spaces for sustainability transformation and reflexive learning. To evaluate this proposal, the authors study already existing active teaching and learning approaches developed within and for ESC and put these in perspective, to define and understand the RWEs.

Insights from a transdisciplinary research project which applied RWEs as a teaching and learning approach in German schools complement conceptual considerations. As a result, advantages, such as the development of core competencies among learners, but also challenges experienced, are illustrated. Though, the challenges found are not unique to the RWE, rather they point out important potentials for ESC through suggesting systematic changes in educational institutions and teaching approaches.

This paper explores RWEs as an active and participatory teaching and learning approach for sustainable consumption education at schools and delivers practical insights and a definition of RWEs as an innovative teaching and learning approach.

Although growing Internet penetration in the hinterlands has attracted agribusinesses to promote digital platforms, farmers are sceptical about using them. The literature discusses agricultural platforms from the theoretical perspective of technological determinism, where the platforms are developed and promoted by firms in a top-down manner to be accepted by farmers. However, this approach results in poorly configured platforms with limited utility for farmers. It is evident from the existing literature that the mere creation of a platform business is not sufficient to guarantee adoption by users. Hence, this study explores how to make the agricultural platform more attractive for farmers.

The present study is based on a discrete choice experiment performed on 126 Indian farmers using agricultural platforms. The data were analysed using the conditional logistic regression method.

The study suggests that farmers expect government and cooperative entities to be also embedded with the platforms. Complementary features such as prompt service, competitive pricing and farm credit were identified as essential attributes. Further, the platforms should enable smallholders to trade farm produce by providing a mechanism for real-time online nudging and bargaining with buyers.

The study is based on the applications of random utility theory. The research has utility for Agtech managers, cooperative institutions and agricultural policymakers.

This is one of the first studies focussing on agricultural platform design from the farmers' perspective. The study implies that incorporating preferred attributes can help practitioners configure platforms to benefit farmers with prospects concerning farm management decisions.

While prior studies have explored the relationship between visual appeal and purchasing decisions, the role of bookmarking has largely been underemphasized. This research aims to address this gap by focusing on the impact of bookmarking on consumer behavior, guided by the cognitive load theory and dual-system theory.

The authors executed a controlled experiment and analyzed the results using a two-stage regression method that linked visual appeal, bookmarking and purchase intent. Further empirical analysis was conducted to authenticate the authors' proposed model, utilizing real-world mobile commerce data from a clothing company.

This study's findings suggest that visual appeal influences purchase intent primarily through the full mediation of bookmarking, rather than exerting a direct influence. Furthermore, an increase in colorfulness corresponds positively with visual appeal, while visual complexity exhibits an inverted U-shaped relationship with it.

This study provides novel insights into the choice-set formation process through the theoretical lens of dual-system theory. Additionally, the authors employed an image processing technique to quantify a product's visual appeal as depicted in a photograph. This study also incorporates a comprehensive econometric analysis to connect the objective aspects of visual appeal with subjective responses.

Circumstances such as pandemics can cause individuals to fall into a state of need, so they turn to donation services for assistance. However, donation services can be designed based on supply-side considerations, e.g. efficiency or inventory control, which restrict consumer choice without necessarily considering how consumer vulnerabilities like low financial or interpersonal power might cause them to react to such restrictions. Thus, the purpose of this paper is to examine service designs that limit the choices consumers are given in terms of either the allowable quantity or assortment variety and examine effects on consumer perceptions of justice and satisfaction.

Three experiments are reported, including one manipulating the service design of an actual food pantry.

When consumers have low financial or interpersonal power, meaning their initial state of control is low, and they encounter a donation service that provides limited (vs. expanded) choice that drops control even lower, they perceive the situation as unjust and report lower satisfaction.

Donation service providers should strive to design services that allow for expanded consumer choice and use interpersonal processes that empower beneficiaries so they perceive the service experience as just and satisfying. Collecting feedback from beneficiaries is also recommended.

While researchers have started to look at the service experiences of vulnerable populations, they have focused primarily on financial service designs. The authors look at donation service designs and identify problems with supply-side limits to choice quantity and assortment.

This study investigated the impacts of the interaction experiential customization (IEC) mode on consumers' information processing fluency and green customization intention (GCI) as well as the moderating effect of consumers' self-construal.

This study conducted an online field experiment, questionnaire study and between-subjects laboratory experiment to test the hypotheses.

It was found that IEC had a significant positive effect on consumers' GCI. Moreover, consumer retrieval processing fluency played a partial mediating role in the relationship between IEC and GCI. In addition, consumers' self-construal moderated the “IEC? Three dimensions of processing fluency” relationships.

The results emphasized the importance of IEC in influencing consumers' consumption intention in a green customization setting and have some practical implications, that is, companies have the opportunity to use appropriate digital choice architecture designs, which can enhance consumer processing fluency when promoting eco-friendly products in the customized consumption process, especially for independent consumers.

This study focused on the customization design on consumers' GCI and explained the mechanism of impact of IEC on improving consumers' processing fluency and GCI in a product customization setting based on the fluency theory. In addition, this study investigated the moderating effect of consumers' self-construal (independent vs interdependent) on their significant different information processing modes for low-carbon choices.

This paper presents a developed BIMxAR application, an integration of building information modeling (BIM) with augmented reality (AR) linked with real-time online database to support the building facility management work. The primary aim of this research was to develop and empirically examine the applicability of a BIM-based AR (BIMxAR) application in building facility management.

The BIMxAR application was developed and experimented with maintenance work of a university laboratory building. The experiment consisted of a comparison of supportive maintenance tasks performed using the traditional approach and the BIMxAR approach by 38 university students. The time taken to complete each task was recorded and analyzed using statistical analyses to compare the performance between the tasks completed using each approach.

The results indicated that the group using the BIMxAR application approach completed the tasks correctly in a significantly shorter time compared to that using the traditional approach. The findings supported the applicability of the developed BIMxAR application and the improvement of the building facility management tasks when using the proposed approach.

This paper presents a methodological approach in developing a mobile application that integrates BIM with AR for facility management work, leveraging real-time information exchange through a cloud-based platform. The paper also provides empirical evidence that demonstrates how the integration between BIM and AR could be achieved and implemented to help facilitate building maintenance tasks.