The good, the bad, and the GPT: Reviewing the impact of generative artificial intelligence on psychology.

This review explores the impact of Generative Artificial Intelligence (GenAI)-a technology capable of autonomously creating new content, ideas, or solutions by learning from extensive data-on psychology. GenAI is changing research methodologies, diagnostics, and treatments by enhancing diagnostic accuracy, personalizing therapeutic interventions, and providing deeper insights into cognitive processes. However, these advancements come with significant ethical concerns, including privacy, bias, and the risk of depersonalization in therapy. By focusing on the current capabilities of GenAI, this study aims to provide a balanced understanding and guide the ethical integration of AI into psychological practices and research. We argue that while GenAI presents profound opportunities, its integration must be approached cautiously using robust ethical frameworks.

Does blockchain technology matter for supply chain resilience in dynamic environments? The role of supply chain integration.

This study aims to empirically investigate the effect of blockchain technology (BCT) adoption on supply chain resilience (SCR), with the mediating role of supply chain integration (SCI) and the crucial effect of environmental dynamism (ED) as a moderator. Based on data collected from firms operating in the automotive industry in India, the proposed model was tested using Partial Least Squares Structural Equations Modelling (PLS-SEM) via SmartPLS software. The empirical results showed a positive effect of BCT on SCI, which in turn affects SCR. Importantly, SCI acts as a full mediator in the BCT-SCR relationship, which is moderated by ED, that is, the effect of BCT on SCR via SCI is strong when ED is high. This study offers the groundwork for operationalizing BCT in a supply chain context. It also contributes to SCR research by investigating how SCI mediates the effect of BCT on SCR. In addition, this study found a moderating effect of ED on the relationship between BCT and SCI. These results provide insights to auto manufacturers on ways to enhance SCR and ensure safe supply chain operations.

Applied artificial intelligence: Acceptance-intention-purchase and satisfaction on smartwatch usage in a Ghanaian context.

Technology and its continuous advancement facilitate human beings to get rid of their criticality and limitation. Applied artificial intelligence (AAI) is one of the latest forms that delimited the limitation of human beings. Smartwatch acts as an applied artificial intelligence to assist various patients to check medical care without going to hospital and physicians. This (three) multiple-study research focused on the intention to use, purchase, and their satisfaction and spread positive word of mouth among others in the Ghanaian. To investigate these issues two renowned theories were underpinned- TAM theory and the Stimulus-Organism-Response (S-O-R). Total 550, 320, and 170 respondents were interviewed with Google forms due to COVID-19 using social media. AI-enabled smartwatch considering Perceived Ease of Use (PEOU), Perceived Usefulness (PU), Perceived Credibility (PC), Perceived Self-Efficacy (PSE), and Perceived Financial Cost (PFC) were significant on intention to adoption and adoption intention on actual purchase. The final study showed device quality, its service level, their usage experience, perceived value, and the extent to which the satisfied customers made positive word of mouth to their friends and family, colleagues and followers. This research is significant in understanding the usage of AI-enabled smartwatches as a device doctor or electronic doctor (e-doctor).

Circular economy of medical waste: novel intelligent medical waste management framework based on extension linear Diophantine fuzzy FDOSM and neural network approach.

Environmental pollution has been a major concern for researchers and policymakers. A number of studies have been conducted to enquire the causes of environmental pollution which suggested numerous policies and techniques as remedial measures. One such major source of environmental pollution, as reported by previous studies, has been the garbage resulting from disposed hospital wastes. The recent outbreak of the COVID-19 pandemic has resulted into mass generation of medical waste which seems to have further deteriorated the issue of environmental pollution. This necessitates active attention from both the researchers and policymakers for effective management of medical waste to prevent the harm to environment and human health. The issue of medical waste management is more important for countries lacking sophisticated medical infrastructure. Accordingly, the purpose of this study is to propose a novel application for identification and classification of 10 hospitals in Iraq which generated more medical waste during the COVID-19 pandemic than others in order to address the issue more effectively. We used the Multi-Criteria Decision Making (MCDM) method to this end. We integrated MCDM with other techniques including the Analytic Hierarchy Process (AHP), linear Diophantine fuzzy set decision by opinion score method (LDFN-FDOSM), and Artificial Neural Network (ANN) analysis to generate more robust results. We classified medical waste into five categories, i.e., general waste, sharp waste, pharmaceutical waste, infectious waste, and pathological waste. We consulted 313 experts to help in identifying the best and the worst medical waste management technique within the perspectives of circular economy using the neural network approach. The findings revealed that incineration technique, microwave technique, pyrolysis technique, autoclave chemical technique, vaporized hydrogen peroxide, dry heat, ozone, and ultraviolet light were the most effective methods to dispose of medical waste during the pandemic. Additionally, ozone was identified as the most suitable technique among all to serve the purpose of circular economy of medical waste. We conclude by discussing the practical implications to guide governments and policy makers to benefit from the circular economy of medical waste to turn pollutant hospitals into sustainable ones.

Resistance to innovation in low-income populations: The case of university students' resistance to using digital productivity applications.

Innovation resistance research remains in its early stages. Efforts to define and comprehend consumer resistance to innovation necessitate in-depth studies that consider the contextual factors of resistance to innovation. To address this challenge, this research explored consumer resistance to innovation in a low-income population, namely, university students on financial support. The innovation under this study is the productivity applications provided for free by the University of Hail, Saudi Arabia, to all students. This study explores variables such as value barrier, risk barrier, tradition barrier, and image barrier and how they impact consumer resistance to innovation in a low-income population. We extend the theory by investigating the moderating roles of consumer characteristics (motivation, self-efficacy, emotion, and attitude toward existing products). The current study is based on an online survey of low-income students at a Saudi Arabian University; 258 cases were gathered. We found that all the direct effects of the variables (i.e., Value Barrier, Risk Barrier, Tradition Barrier, and Image Barrier) were positively related to consumer resistance to innovation. Importantly, consumer characteristics significantly moderate this relationship, as the relationship is stronger when the measurements for consumer characteristics are high.

The Swedish gamble: trust in the government and self-efficacy in the battle to combat COVID-19.

Governments around the world have issued movement restrictions and quarantines to combat the SARS-CoV-2 (COVID-19) pandemic. However, the Swedish government has not implemented such measures but has depended on individual responsibility. The extent to which individuals have been encouraged to trust in and be satisfied with government strategies and adopt personal health measures, such as social isolation, remains unclear. This study examines the direct effects of trust in the government and risk perception on self-efficacy. Most importantly, this study intends to explore whether satisfaction with government measures strengthens the relationships between 1) trust in the government and self-efficacy and 2) risk perception and self-efficacy. We test our suggested hypotheses using survey data obtained from 403 Swedish citizens living in Sweden. As predicted, the findings indicate that trust in the government and risk perception positively impact individual self-efficacy. Additionally, the findings reveal that satisfaction with government measures strengthens these relationships; more precisely, the impact of trust in the government and risk perception under a high level of individual satisfaction with government measures is much more positive than that under a low satisfaction level. In practice, a focus on implementing successful policies and excellent individual self-efficacy is required to halt the pandemic, and the findings indicate that combining strictly attentive and adaptive individual strategies with government strategies can minimize the spread of infection.

Applied Artificial Intelligence and user satisfaction: Smartwatch usage for healthcare in Bangladesh during COVID-19.

The evolution of Artificial Intelligence (AI) has revolutionized many aspects of human life, including healthcare. Amidst the Covid-19 pandemic, AI-enabled smartwatches are being used to help users to self-monitor and self-manage their health. Using a framework based on Stimulus-Organism-Response (S-O-R) theory, this present study aimed to explore the use of AI-enabled smartwatches for health purposes, in particular the effects of product quality, service quality, perceived convenience, and perceived ease of use on user experience, trust and user satisfaction. Based on a purposive survey sample of 486 smartphone users in Bangladesh, data collected was analyzed using SPSS software for elementary analyses and PLS-SEM for hypotheses testing. The findings showed that the predictors, namely product quality, service quality, perceived convenience, and perceived ease of use, significantly affected user experience and trust. Similarly, user experience and trust were influential on user satisfaction and played partial mediating roles between predictors and user satisfaction. Besides, gender and age moderate the relationships of experience and trust with customer satisfaction. These findings support the S-O-R theoretical framework and have practical implications for brand and marketing managers of smartwatches in developing product features and understanding users' attitudes and behaviours.

How Upper/Middle Managers' Ethical Leadership Activates Employee Ethical Behavior? The Role of Organizational Justice Perceptions Among Employees.

Several studies have been conducted on ethical leadership and workplace ethical behavior but little is known about the role of organizational justice and each of its dimensions (procedural, distributive, interpersonal, informational) in this relationship. This study predicts that ethical leadership enhances organizational justice perceptions, including each of its specific dimensions, which in turn enhances employee ethical behavior. The results from two-wave survey data obtained from 270 employees in the Malaysian manufacturing industry confirm that ethical leadership has a positive impact on employee ethical behavior, and that organizational justice and each of its justice dimensions mediate this relationship, both individually and together. Importantly, interpersonal and informational dimensions show the strongest mediation effects. This paper highlights the actions and strategies that can help managers to effectively elevate the moral tone in their organizations. In particular, our findings show where managers must put more emphasis to foster an ethical workplace: on providing fair treatment (interpersonal justice) and honest information (informational justice).

Does quality stimulate customer satisfaction where perceived value mediates and the usage of social media moderates?

Customer is considered as the king in the world of business. The issue of customer satisfaction in electronics home appliances has received greater attention from academics and practitioners. In other words, customer satisfaction is a vital consideration in marketing. With the development of technology, new and innovative electronic home appliances are available in the market. Customers purchase and use the costly electronic home appliances where the satisfaction issue is an important concern. In Bangladesh, working families find the electronic home appliance very necessary. Companies offer state-of- the-art appliances for customers' household works. Therefore, the study intends to investigate the effect of product quality (PQ), quality of service (SQ) and perceived value on customer satisfaction (CS). In addition, this study also seeks this relationship shaped by customer's perceived value (CPV) as a key mechanism and interacted by social media usage. A total of 300 households were selected on a judgmental basis from Dhaka city in Bangladesh using a structured questionnaire. Collected data were CB-SEM (AMOS-v24) and SPSS. The findings showed PQ and SQ have positive effects on CS; SQ affects, but PQ does not affect CPV. CPV has a mixing mediating effect on SQ and CS relationship and PQ and CS relationship. Importantly, the positive impact of PQ, SQ and CPV is greater on customers who exhibit higher social media use. The conceptual framework was buttressed by EDT theory. The study contributed to contextual and theoretical knowledge in regards to home appliances. The practicing managers can collect an insight of customer satisfaction for their business.