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Our understanding of what intervention strategies are effective in improving the well-being of older adults experiencing elder abuse and self-neglect (EASN) is severely limited. The purpose of this study was to examine the use of a method called “teaming,” a wraparound approach to provide enhanced social support to older adults experiencing EASN. A teaming intervention was administered by advocates in Maine, USA, as a component of a larger community-based EASN intervention, Repair harm, Inspire change, Support connection, Empower choice (RISE), implemented to complement adult protective services.

Qualitative interviews and a focus group were conducted with RISE advocates (n = 4). A descriptive phenomenological approach involving two independent assessors was used to code transcripts into themes and subthemes.

Three domains were identified: (1) team and support forming process, which describes the development of a supportive network based on each client’s needs; (2) techniques, which refers to the specific strategies advocates use to promote collectivity and shared responsibility around the client; and (3) implementation challenges, which discusses the difficulties advocates encounter when using teaming with people experiencing EASN.

This study represents the first in-depth exploration of teaming in the context of EASN intervention. Preliminary findings on the experiences of advocates suggest that teaming is a beneficial approach to support the individualized needs of each client, and to promote improved and sustainable case outcomes for clients.

When retail businesses, especially small businesses with greater vulnerability, could not meet consumers in person during the recent pandemic crisis, how did they adapt to the situation? This study examined how small business practitioners (SBPs’) perceptions, trust and adoption intention levels for social media, as well as the relationships among these variables, changed before and during the crisis based on the integration of the contingency theory and the diffusion of innovation theory (DIT).

Online surveys were conducted with USA SBPs before (n = 175) and during (n = 225) the recent pandemic. The hypotheses were tested using structural equation modeling (SEM), multivariate analysis of variance (MANOVA) and multiple-group SEM analysis.

The results confirmed significant sequential positive relationships between SBPs’ perceived external pressure and perceived benefits of adopting social media, which in turn led to their trust in and then adoption intentions for social media. Further, the comparisons between the pre- and in-pandemic samples revealed that SBPs’ perceptions and adoption intentions all became significantly higher during (vs before) the pandemic, but the structural relationships among these variables weakened during the pandemic.

This study uses a novel approach to integrate the contingency theory with the DIT to propose small businesses' perceptions, trust and adoption intentions for social media during the innovation decision process under rapid contingency changes. Our findings also offer practical implications including recommendations for small businesses’ innovation management as well as training programs.

Consumers worldwide are increasingly adopting mobile payments. However, despite its global popularity, this innovation did not diffuse among American consumers extensively. As of 2019, less than 30% of smartphone users in the USA engaged in mobile payments. The purpose of this paper is to investigate drivers of mobile payment adoption in the USA and to explore the mediating factors of consumers’ attitudes toward mobile payments.

Data were collected through Amazon M-Turk in the USA with 222 final respondents. Participants received an incentive to participate in this study. The measurement and structural models were evaluated by the component-based partial least squares (PLS) approach using Smart-PLS 3 software.

The study shows several factors affecting consumers’ attitudes toward mobile payments. Specifically, relative advantage, compatibility, observability, perceived security and convenience influence attitudes toward mobile payments and, consequently, behavioral intent to use mobile payment technology. This investigation contributes to the ongoing inquiry on the adoption of mobile payment technology in the USA. It offers specific insights for managers on how to increase mobile payment adoption. The study establishes a modified diffusion of innovations (DOI) model of consumer attitudes toward the use of mobile payments.

The objective of this study is to focus mainly on consumers in the USA, and it limits the generalizability of this study.

This study contributes to the current research on mobile payment adoption. Based on theoretical considerations, the authors derived a research model specifying critical drivers of an individual’s intentions to use mobile payments. Specifically, we establish a modified DOI-based model of consumer attitudes towards mobile payments. It shows several contributing factors affecting consumers’ attitudes toward mobile payments. The paper has important managerial implications aimed at the increase of the diffusion of mobile payments in the USA.

This study aims to identify the determinants of adopting financial technology (FinTech) in Haryana (India). Further, the authors also compare the behavioural intention among male and female respondents to deliver a comprehensive understanding of the adoption of FinTech.

The current study contains two cross-sectional surveys about males and females. Study M is completed with (333) males, and Study F is conducted on (317) female users towards FinTech adoption. This study used “Partial least squares-structural equation modelling (PLS-SEM)” for data analysis.

The outcomes indicate that in both (Studies M and F), perceived usefulness and perceived ease of use substantially impact attitude and behavioural intention. Moreover, the results show that perceived value significantly influences, while perceived risks insignificantly influence behavioural intention. Surprisingly, relative advantage (in Study M) and trialability (in Study F) has insignificant impact on behavioural intention. Further, the outcomes also confirm that in both studies (M and F), attitude and behavioural intention substantially influence the actual use of FinTech.

To the best of the authors’ knowledge, this is the preliminary research on FinTech to inspect the role of gender in the technology adoption process. The adoption difference between males and females and the insightful result that the authors found help shed light on the uniqueness of the context. This study is also one of the initial to test three credible technology determinant theories and then offer a robust model for the actual use of FinTech that is to be used by both practitioners and researchers.

This paper investigates a problem in a reverse logistics (RLs) network to decide whether to dispose of unsold goods in primary stores or re-commercialize them in outlet centers. By deducting the costs associated with each policy from its revenue, this study aims to maximize the profit from managing unsold goods.

A new mixed-integer linear programming model has been developed to address the problem, which considers the selling prices of products in primary and secondary stores and the costs of transportation, cross-docking and returning unwanted items. As a result of uncertain nature of the cost and time parameters, gray numbers are used to deal with it. In addition, an innovative uncertain solution approach for gray programming problems is presented that considers objective function satisfaction level as an indicator of optimism.

According to the results, higher costs, including transportation, cross-docking and return costs, make sending goods to outlet centers unprofitable and more goods are disposed of in primary stores. Prices in primary and secondary stores heavily influence the number of discarded goods. Higher prices in primary stores result in more disposed of goods, while higher prices in secondary stores result in fewer. As a result of the proposed method, the objective function satisfaction level can be viewed as a measure of optimism.

An integral contribution of this study is developing a new mixed-integer linear programming model for selecting the appropriate goods for re-commercialization and choosing the best outlet center based on the products' price and total profit. Another novelty of the proposed model is considering the matching percentage of boxes with secondary stores’ desired product lists and the probability of returning goods due to non-compliance with delivery dates. Moreover, a new uncertain solution approach is developed to solve mathematical programming problems with gray parameters.