Search results

Corporate social responsibility (CSR) activities of companies have been reported to generate favorable consumer attitudes towards the business, which in turn, encourages positive consumer behavior. But the application of this conclusion in the mobile commerce domain remains limited. Drawing on social exchange theory, the authors examined the mediating role of trusting beliefs and satisfaction in the relationship between CSR and purchase intention in mobile commerce.

Using nonprobability convenience sampling, the authors administered a cross-sectional survey with 314 students from Keimyung University in Korea. Initially, SPSS-Amos was utilized to run confirmatory factor analysis. The proposed hypotheses were tested using structural equation modeling.

This study showed that two components of trusting beliefs, namely benevolence and competence, had a positive effect on the association between CSR and the purchase intention on mobile shopping applications. This relationship was partially mediated by trusting beliefs. Further findings demonstrated that the impact of CSR on purchase intention was also partially mediated by satisfaction.

The authors' contribution includes extending the social exchange theory to the mobile commerce setting by establishing mechanisms that explain the ways CSR influences purchase intention in the mobile commerce framework. The authors integrated trusting beliefs and satisfaction in the CRS chain link with purchase intention. Additionally, the authors examined the individual effects of three trusting beliefs components. Based on the results, the authors proposed suggestions for the mobile shopping application business on the methods they can implement to boost the outcomes of their CSR activities.

:過去的研究結果、均顯示公司的企業社會責任行為會產生對公司良好的消費者態度,而這消費者態度,則進而促進積極的消費行為; 唯這結論的應用、在移動商務的領域內仍是有限的。我們利用社會交換理論、探討了信任的信念和滿意在移動商務裡的企業社會責任與購買意圖之間的關係上的中介角色。

:透過使用非機率便利抽樣的研究法,我們對來自南韓啟明大學314名學生進行了一個橫向調查研究。最初,我們使用結構方程模型 (SPSS-AMOS) 來進行驗證性因素分析。又用結構方程模型 (SEM) 來為提出的假設進行測試。

:研究結果顯示,信任的信念的兩個組成部分,即仁愛和能力,均於移動購物應用上對企業社會責任與購買意圖之間的關聯有積極正面的影響。這關聯部分上為信任的信念所調節。研究結果更表明了企業社會責任對購買意圖的影響、亦是部分上為滿意所調節的。

:本研究的貢獻、包括藉著建立一個可解釋企業社會責任、如何在移動商務的框架裡影響購買意圖的機制,去把社會交換理論擴展至移動商務的環境。我們在企業社會責任與購買意圖一連串的關聯裡、融入了信任的信念和滿意。而且,我們探討了三個信任的信念的組成部分各自所帶來的影響。我們根據研究的結果,為移動購物應用之商業機構,建議有效的方法,去增強其企業社會責任行為的效果。

Hospitality firms aim to increase their profits by implementing a variety of marketing activities, including using decoy pricing to provide alternative choices for consumers. Decoys are relatively higher-priced offerings that signal lower value than the other offerings in the consideration set. The purpose of this research is to investigate the influence of decoy pricing on consumer choices across various contexts in the foodservice and hotel industries.

Across the pilot and four main studies, the current research employs a sequential exploratory mixed-method design to investigate the influence of decoy pricing in the foodservice and lodging industries. The qualitative part of this research was based on two focus groups, followed by a pilot study and four main study experiments.

The results show that decoy pricing escalates consumers’ choices of more expensive product bundles in both restaurant and hotel cancellation policy contexts. However, decoy pricing does not increase the selection of more expensive hotel product bundles.

While decoy pricing has been utilized as an effective revenue maximization strategy for product placement in retail stores, less is known about how promotional advertisements with decoy offers influence hotel and restaurant customers to choose more costly options. Specifically, this is the first study that explores whether decoy pricing and product/service bundling can encourage customers to select more expensive offers in hotel and restaurant contexts, considering the types of hospitality bundles that may limit this effect.

Publicly available datasets in the USA present data suppression issues that limit the ability to investigate entrepreneurial subgroups like military veterans, which account for about one in ten entrepreneurs in the USA. Thus, despite public desire to support veteran entrepreneurs (“vetrepreneurs”), there is a limited descriptive understanding on the relationship between veteran business owner demographics, such as gender and race, and their business survival and growth. We address this limited understanding in this article by providing descriptive evidence on veteran-owned business survival and growth, emphasizing variation across race and gender.

We use limited-access longitudinal microdata to provide descriptive evidence on the survival and growth of veteran-owned firms across race and gender.

Findings indicate statistically significant variation across demographic subgroups’ business survival and employment growth. For example, veteran-owned firms have high women ownership rates, greater employment, revenues and payrolls, but also lower employment and revenue growth. More generally we provide descriptive evidence that military experience or the military community help women overcome the gender gap in small business survival.

This type of descriptive research is common among entrepreneurial researchers, however, peer-reviewed research specific to US veterans is very limited. These descriptive results are useful for policymakers and for spurring future policy research related to veteran entrepreneurs.

The US platelet supply is almost exclusively dependent on apheresis donors who are “aging out.” As a result, blood centers and hospitals have been experiencing spot shortages and have resorted to transfusing low-dose platelets. This paper explores using whole blood–derived platelets (WB-PLTs) to supplement the apheresis platelet (APH-PLT) supply.

This paper reviews the history leading to the current state of the US platelet supply and includes the impact of recent events such as the COVID-19 pandemic and the implementation of the US Food and Drug Administration (FDA)-mandated bacterial mitigation strategies.

WB-PLTs represent a viable source of platelets that can be used to supplement the APH-PLT supply. Whole blood automation represents a new methodology to more easily prepare WB-PLTs. Advances in donor testing and screening as well as pre-storage leukoreduction have improved the safety of WB-PLTs to the same level as APH-PLTs. Blood services in the US and abroad transfuse WB-PLTs interchangeably in all patient populations.

This paper highlights how the US blood industry is essentially “sole-sourced” in terms of APH-PLTs. In this post-COVID-19 period, when most industries are building redundancies in their supply chains, blood centers should consider WB-PLTs as an additional source of platelets to bolster the US platelet supply.

Data breaches in the US healthcare sector have more than tripled in the last decade across all states. However, to this day, no established framework ranks all states from most to least at risk for healthcare data breaches. This gap has led to a lack of proper risk identification and understanding of cyber environments at state levels.

Based on the security action cycle, the National Institute of Standards and Technology (NIST) cybersecurity framework, the risk-planning model, and the multicriteria decision-making (MCDM) literature, the paper offers an integrated multicriteria framework for prioritization in cybersecurity to address this lack and other prioritization issues in risk management in the field. The study used historical breach data between 2015 and 2021.

The findings showed that California, Texas, New York, Florida, Indiana, Pennsylvania, Massachusetts, Minnesota, Ohio, and Georgia are the states most at risk for healthcare data breaches.

The findings highlight each US state faces a different level of healthcare risk. The findings are informative for patients, crucial for privacy officers in understanding the nuances of their risk environment, and important for policy-makers who must grasp the grave disconnect between existing issues and legislative practices. Furthermore, the study suggests an association between positioning state risk and such factors as population and wealth, both avenues for future research.

Theoretically, the paper offers an integrated framework, whose basis in established security models in both academia and industry practice enables utilizing it in various prioritization scenarios in the field of cybersecurity. It further emphasizes the importance of risk identification and brings attention to different healthcare cybersecurity environments among the different US states.

The COVID-19 pandemic dramatically affected the fire service: stay-at-home orders and potential exposure hazards disrupted standard fire service operations and incident patterns. The ability to predict incident volume during such disruptions is crucial for dynamic and efficient staff allocation planning. This work proposes a model to quantify the relationship between the increase in “residential mobility” (i.e. time spent at home) due to COVID-19 and fire and emergency medical services (EMS) call volume at the onset of the pandemic (February – May 2020). Understanding this relationship is beneficial should mobility disruptions of this scale occur again.

The analysis was run on 56 fire departments that subscribe to the National Fire Operations Reporting System (NFORS). This platform enables fire departments to report and visualize operational data. The model consists of a Bayesian hierarchical model. Text comments reported by first responders were also analyzed to provide additional context for the types of incidents that drive the model’s results.

Overall, a 1% increase in residential mobility (i.e. time spent at home) was associated with a 1.43% and 0.46% drop in EMS and fire call volume, respectively. Around 89% and 21% of departments had a significant decrease in EMS and fire call volume, respectively, as time spent at home increased.

A few papers have investigated the impact of COVID-19 on fire incidents in a few locations, but none have covered an extensive number of fire departments. Additionally, no studies have investigated the relationship between mobility and fire department call volumes.

This real estate insight provides a comprehensive analysis of the current state and future potential of tokenization in the real estate industry mentioning several challenges to overcome to take advantage of this technology. We highlight potential benefits, including enhanced liquidity, increased security and improved accessibility. Additionally, the real estate insight critically discusses potential drawbacks, such as regulatory challenges and technological risks, and explores the impact of tokenization on real estate prices.

This real estate insight employs a comprehensive literature review alongside a qualitative analysis of various case studies to explore current implementations of tokenization within the real estate industry. Multiple applications of tokenization in the real estate industry are examined, including fractional ownership, property management and transaction processes. The study investigates the optimization potential of tokenization for asset liquidity in the real estate area, transaction transparency and security. It also critically discusses potential challenges, such as regulatory compliance, security vulnerabilities and market adoption.

The future of real estate tokenization, driven by blockchain technology and smart contracts, offers significant potential for growth, enhancing liquidity and accessibility through fractional ownership. Smart contracts automate and secure transactions, while evolving standards and regulatory frameworks in regions like North America, Europe and Asia support market expansion. Since its initial implementation with the St. Regis Aspen Resort STO, a stream of successful projects has highlighted the viability of tokenization. However, challenges remain, including the need for regulatory clarity, industry and customer education, displacements of market participants and jobs and environmental impacts. Integrating advanced technologies like AI and IoT can further streamline property management and investment decisions.

The real estate insight’s practical implications extend to industry professionals, policymakers and technology developers. Professionals gain insights into how tokenization can enhance liquidity and security in the real estate sector, guiding strategic decision-making. For policymakers, understanding potential challenges like regulatory compliance and technological risks informs the development of supportive regulations. Technology developers can also benefit from understanding the sector-specific applications and concerns raised. Highlighting the need for robust security measures and regulatory compliance in tokenization systems may foster better design practices. Therefore, the real estate insight’s findings could significantly shape the future development of tokenization integration in the real estate industry.

This real estate insight offers original value through a comprehensive analysis of the current and future impacts of tokenization in the real estate industry. It examines various applications of tokenization and critically discusses the potential challenges. The focus on informing strategic decisions for professionals and policymakers enhances its utility as a resource. Additionally, by addressing both the benefits and drawbacks, this study contributes to the broader discourse on the societal implications of tokenization. In the context of rapid technological advancement, such thorough studies are rare, further underscoring the real estate insight’s originality.

This case study paper aims to explore the complexities and challenges of epidemic response and public health surveillance in Native American and Indigenous American communities in the United States and find viable solutions. This paper explores these topics through the emergence and impact of the hantavirus pulmonary syndrome (HPS) within the Navajo Nation in the United States using critical incident analysis and best practices.

This project is a case study paper based on a topical review of the literature. A topical review of the literature is a comprehensive exploration of the current body of knowledge within a particular research field. It is an important tool used by scholars and practitioners to further the development of existing knowledge as well as to identify potential directions for future research (Fourie, 2020). Such a paper can provide a useful insight into the various aspects of the process that the researcher may have overlooked, as well as highlighting potential areas of improvement (Gall et al., 2020). It can also provide a useful source of ideas and inspiration for the researcher as it can provide an overview of the various approaches used by other researchers in the field (Göpferich, 2009). Case study papers using a topical review of the literature have been used to help frame and inform research topics, problems and best practices for some time. They are typically used to explore a topic in greater depth and to provide an overview of the literature to improve the world of practice to provide a foundation for future comprehensive empirical research. Case study papers can provide research value by helping to identify gaps in the literature and by providing a general direction for further research. They can also be used to provide a starting point for research questions and hypotheses and to help identify potential areas of inquiry.

This study explores best practices in public health surveillance and epidemic response that can help strengthen public health infrastructure by informing the development of effective surveillance systems and emergency response plans, as well as improving data collection and analysis capabilities within Native American and Indigenous American communities in the United States that also have the option to include new technologies like artificial intelligence (AI) with similar outbreaks in the future.

The literature review did not include any primary data collection, so the existing available research may have limited the findings. The scope of the study was limited to published literature, which may not have reported all relevant findings. For example, unpublished studies, field studies and industry reports may have provided additional insights not included in the literature review. This research has significant value based on the limited amount of studies on how infectious diseases can severely impact Native American communities in the United States, leading to unnecessary and preventable suffering and death. As a result, research on viable best practices is needed on the best practices in public health surveillance and epidemic response in Native American and Indigenous American communities through historical events and critical incident analysis.

Research on public health surveillance and epidemic response in Native American communities can provide insights into the challenges faced by these communities and help identify potential solutions to improve their capacity to detect, respond to and prevent infectious diseases using innovative approaches and new technologies like AI.

More research on public health surveillance and epidemic response can inform policies and interventions to improve access to healthcare for Native American populations, such as increasing availability of healthcare services, providing culturally appropriate health education and improving communication between providers and patients. By providing better public health surveillance and response capacity, research can help reduce the burden of infectious diseases in Native American communities and ultimately lead to improved public health outcomes.

Recent evidence from a linear econometric framework infers that housing search activity, captured from Google Trends data, can predict housing returns for the USA at a national and regional (metropolitan statistical area [MSA]) level. Based on search theory, the authors, however, postulate that search activity can also predict housing returns volatility. This study aims to explore the possibility of using online search activity to predict both housing returns and volatility.

Using a k-th order non-parametric causality-in-quantiles test allows us to test for predictability in a robust manner over the entire conditional distribution of both housing price returns and its volatility (i.e. squared returns) by controlling for nonlinearity and structural breaks that exist in the data.

The analysis over the monthly period of 2004:01 to 2021:01 produces results indicating that while housing search activity continues to predict aggregate US house price returns, barring the extreme ends of the conditional distribution, volatility is relatively strongly predicted over the entire quantile range considered. The results carry over to an alternative (the generalized autoregressive conditional heteroskedasticity-based) metric of volatility, higher (weekly)-frequency data (over January 2018–March 2021) and to over 84% of the 77 MSAs considered.

To the best of the authors’ knowledge, this is the first study regarding predictability of overall and regional US housing price returns and volatility using search activity, based on a non-parametric higher-order causality-in-quantiles framework, which is insightful to investors, policymakers and academics.

The authors designed a science and engineering curricular program that includes design features that promote student interest and motivation and examined teachers' and students' views on meaningfulness, motivation and interest.

The research approach consisted of mixed methods, including content analyses and descriptive statistics.

The curricular program successfully included all four of the US National Academies of Sciences' design features for promoting interest and motivation through scientific investigation and engineering design. During interviews, teachers and students expressed evidence of design features associated with interest and motivation. After experiencing the program, more than 60% of all students scored high on all four science and engineering meaningfulness and interest survey items.

A curricular program that extends science learning through the engineered design of solutions is an innovative approach to foster both conceptual knowledge development and interest and motivation in science and engineering.