Examining the key determinants of the jordanian customer's adoption of genetically modified food

Genetically modified food (GMF) is one of the most debated issues in the food market. There has been considerable interest from both academic researchers and policy makers regarding the antecedents and consequences of the commercial adoption of GMF applications. Conceptually, GMF can be defined as "Genetically modified (hereafter GM) foods are produced from genetically modified seeds or ingredients derived from plants or animals whose DNA has been manipulated using genetic engineering methods" [1, p. 2861]. However, only a limited number of studies have tested the related issues of GMF products from a customer perspective. Thus, this project intends to discover and examine the main drivers and hindrances in predicting customers' intention and buying decision behaviour in developing Arabian countries (i.e., Jordan). A diffusion of innovations (DOIs) model was selected as the theoretical basis for the current study project. A field survey study was conducted to collect the requested quantitative data from a convenience sample of Jordanian customers. Statistical results largely supported the role of relative advantage, compatibility, trialability, social approval, awareness, perceived risk and price value on the behavioural intention to adopt GMF products, which in turn significantly predicted actual adoption behaviour. The results of the current project will hopefully expand the current academic understanding of the main factors that predict Jordanian customers' perception and adoption of GMF products.This research project (Project ID DSR-2020#239) was funded by Al-Balqa Applied University . We would like to express our sincere gratitude and appreciation to Al-Balqa Applied University for its invaluable support and generous contribution towards our project.Scopu

“So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts

“So what if ChatGPT wrote it?”:Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy

Transformative artificially intelligent tools, such as ChatGPT, designed to generate sophisticated text indistinguishable from that produced by a human, are applicable across a wide range of contexts. The technology presents opportunities as well as, often ethical and legal, challenges, and has the potential for both positive and negative impacts for organisations, society, and individuals. Offering multi-disciplinary insight into some of these, this article brings together 43 contributions from experts in fields such as computer science, marketing, information systems, education, policy, hospitality and tourism, management, publishing, and nursing. The contributors acknowledge ChatGPT’s capabilities to enhance productivity and suggest that it is likely to offer significant gains in the banking, hospitality and tourism, and information technology industries, and enhance business activities, such as management and marketing. Nevertheless, they also consider its limitations, disruptions to practices, threats to privacy and security, and consequences of biases, misuse, and misinformation. However, opinion is split on whether ChatGPT’s use should be restricted or legislated. Drawing on these contributions, the article identifies questions requiring further research across three thematic areas: knowledge, transparency, and ethics; digital transformation of organisations and societies; and teaching, learning, and scholarly research. The avenues for further research include: identifying skills, resources, and capabilities needed to handle generative AI; examining biases of generative AI attributable to training datasets and processes; exploring business and societal contexts best suited for generative AI implementation; determining optimal combinations of human and generative AI for various tasks; identifying ways to assess accuracy of text produced by generative AI; and uncovering the ethical and legal issues in using generative AI across different contexts

An integrated model for using social media applications in non-profit organizations

The growing social media use worldwide has encouraged researchers to research on how and why it is adopted. However, the majority of studies have focused on the individual rather than the organizational level. There is also a relative paucity of research on organizational level factors that affect the use of social media applications by non-profit organizations (NPOs). Hence, this study aims to bridge this gap in research by analyzing the factors that determine social media use, which leads to increasing the effectiveness (i.e., awareness, community engagement, and fundraising) of NPOs. The data were collected through questionnaires distributed to public relations practitioners in 325 NPOs in Jordan and analyzed using structural equation modeling (SEM). The results supported the vital role of performance expectancy, effort expectancy, facilitating conditions, social influence, and management commitment on the actual usage of social media. The results also showed that using social media has a significant positive effect on awareness and community engagement, while no significant impact is reported regarding fundraising. Theoretically, this study extends the unified theory of acceptance and use of technology (UTAUT) by incorporating new factors, namely management commitment, awareness, community engagement, and fundraising, and proposing new relationships in the model. Practically, this research provides implications for stakeholders of NPOs, including policymakers and public relations practitioners