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PurposeDuring COVID-19 pandemic, the use of social media enhances information exchange at a global level; therefore, customers are more aware and make backup plans to take optimal decisions. This study explores the customer psychology of impulse buying during COVID-19 pandemic.Design/methodology/approachThe researcher, being a social constructionist, aims at understanding social patterns in impulsive buying strategies during COVID-19 pandemic. Forty UK consumers were participated using the telephonic interview method with the purpose to maintain social distancing practices.FindingsResults revealed that vulnerable group of people, fear of illness, fear of empty shelves, fear of price increase and social inclination to buy extra for staying at home, increased panic impulsive buying behaviour among customers. Many people socially interpreted the evidence of death rate and empty shelves, which led to more disinformation, rumours and sensationalism, which increased customers' impulsive buying behaviour. Finally, risk of going outside, COVID-19 outbreak among employees of local retail stores, and health professionals' recommendations to stay at home, led to impulsive buying behaviour.Originality/valueThis study has constructed a research framework of customer psychology of impulse buying based on the results of this study and fear and perceived risk theories. The study also explains how the fear of fear, risk perception and conformist tendency enhanced impulsive buying during COVID-19 pandemic. This study has discussed specific implications for retailers.

Thematic analysis is a highly popular technique among qualitative researchers for analyzing qualitative data, which usually comprises thick descriptive data. However, the application and use of thematic analysis has also involved complications due to confusion regarding the final outcome’s presentation as a conceptual model. This paper develops a systematic thematic analysis process for creating a conceptual model from qualitative research findings. It explores the adaptability of the proposed process across various research methodologies, including constructivist methodologies, positivist methodologies, grounded theory, and interpretive phenomenology, and justifies their application. The paper distinguishes between inductive and deductive coding approaches and emphasizes the merits of each. It suggests that the derived systematic thematic analysis model is valuable across multiple disciplines, particularly in grounded theory, ethnographic approaches, and narrative approaches, while also being adaptable to more descriptive, positivist-based methodologies. By providing a methodological roadmap, this study enhances the rigor and replicability of thematic analysis and offers a comprehensive strategy for theoretical conceptualization in qualitative research. The contribution of this paper is a systematic six-step thematic analysis process that leads to the development of a conceptual model; each step is described in detail and examples are given.

PurposeThis study aims to examine the relationship between green human resource management (GHRM) practices and green transformational leadership toward inducing employees' green creativity. Specifically, drawing upon the ability, motivation and opportunity theory, the authors tested how green perceived organizational support (green POS) mediates the link between GHRM practices and employees' green creativity. Furthermore, based on the firm's resource-based view, the authors examine the moderating role of green transformational leadership on the relationship between GHRM practice and green POS.Design/methodology/approachUsing a survey questionnaire, this research was conducted with a multi-source sample of 201 supervisors and their 428 subordinates from organizations working in grocery, food and personal care products in Pakistan.FindingsThe findings of structural equation modeling revealed that green POS plays a mediating role between GHRM and employees' green creativity. The study findings also highlighted that green transformational leadership moderates the positive relationship between GHRM practices and green POS.Practical implicationsOrganizations need to implement GHRM practices to achieve environmental performance. Individuals are likely to recognize themselves with organizations that are engaged in green practices, and therefore, organizations can get benefits from implementing GHRM practices.Originality/valueThis research explores green POS and green transformational leadership as novel mechanisms through which GHRM practices influence employees' green creativity in organizations. In addition, the authors empirically examined our theorized relationships in the South Asian context.

The concept of saturation in qualitative research is a widely debated topic. Saturation refers to the point at which no new data or themes are emerging from the data set, which indicates that the data have been fully explored. It is considered an important concept as it helps to ensure that the findings are robust and that the data are being used to their full potential to achieve the research aim. Saturation, or the point at which further observation of data will not lead to the discovery of more information related to the research questions, is an important aspect of qualitative research. However, there is some mystification and semantic debate surrounding the term saturation, and it is not always clear how many rounds of research are needed to reach saturation or what criteria are used to make that determination during the thematic analysis process. This paper focuses on the actualisation of saturation in the context of thematic analysis and develops a systematic approach to using data to justify the contribution of research. Consequently, we introduce a distinct model to help researchers reach saturation through refining or expanding existing quotations, codes, themes and concepts as necessary.

This review explores the role of probiotics in improving productivity and gut health in poultry through microbiome modulation, particularly during early life. Gut health is pivotal to poultry performance, influencing nutrient absorption, immune function, and disease resistance. Early-life interventions target the microbiome to shape long-term health and productivity. Probiotics, live microorganisms providing health benefits, improve gut health through the competitive exclusion of pathogens, immune modulation, antimicrobial compound production, and enhancing gut barrier integrity. Applying probiotics improves growth performance, feed conversion efficiency, body weight gain, and carcass quality by promoting lean muscle growth and reducing fat deposition. For laying hens, probiotics enhance egg production and quality. These benefits are linked to better nutrient utilization, a well-balanced microbiome, and reduced gastrointestinal disorders. However, the efficacy of probiotics depends on strain specificity, dosage, and administration methods. Factors like environmental conditions, storage stability, and interactions with other feed additives also influence their effectiveness. Despite these challenges, advancements in microbiome research and probiotic technologies, such as precision probiotics and synbiotics, provide promising solutions. Future research should focus on optimizing formulations, understanding host–microbiome interactions, and leveraging new technologies for targeted microbiome management.

This study sets out how to use generative artificial intelligence (AI) in the six steps of systematic thematic analysis. It leverages AI to address the limitations of traditional thematic analysis. This paper developed prompts (inputs) for ChatGPT (a generative AI chatbot based on a large language model) that are based on many researchers’ discussions and criticisms of qualitative data analysis. The contributions of this paper are twofold. First, it addresses a critical research gap by showcasing ChatGPT prompts for each step of the six steps of systematic thematic analysis, which also addresses researcher training in thematic analysis. Second, it contributes to the development of input to train AI in thematic analysis, including a description of how to familiarize an AI system with the context of a research study and the researcher’s methodological and theoretical considerations; this approach helps to reduce human bias and improves accountability and transparency in thematic analysis.

There is a continuous need to design and develop wireless technologies to meet the increasing demands for high-speed wireless data transfer to incorporate advanced intelligent transport systems. Different wireless technologies are continuously evolving including short-range and long-range (WiMAX, LTE, and 5G) cellular standards. These emerging technologies can considerably enhance the operational performance of communication between vehicles and road-side infrastructure. This paper analyzes the performance of cellular-based long-term evolution (LTE) and 5GTN (5G Test Network) in pilot field measurements (i.e., vehicle-to-vehicle and vehicle-to-infrastructure) when delivering road weather and traffic information in real-time environments. Measurements were conducted on a test track operated and owned by the Finnish Meteorological Institute (FMI), Finland. The results showed that 5GTN outperformed LTE when exchanging road weather and traffic data messages in V2V and V2I scenarios. This comparison was made by mainly considering bandwidth, throughput, packet loss, and latency. The safety critical messages were transmitted at a transmission frequency of 10 Hz. The performance of both compared technologies (i.e., LTE and 5GTN) fulfilled the minimum requirements of the ITS-Assisted Road weather and traffic platform to offer reliable communication for enhanced road traffic safety. The field measurement results also illustrate the advantage of cellular networks (LTE and 5GTN) with a clear potential to use it heterogeneously in future field tests with short-range protocols, e.g., IEEE 802.11p.

This paper studies the connectedness between oil price shocks and agricultural commodities. Our sample period ranges from January 2002 to July 2020, covering the three global crises; Global Financial Crisis, the European sovereign debt crisis and Covid-19 pandemic crisis. We employ Granger causality tests, and the static and dynamic connectedness spillover index methodology. We find that the shocks in oil prices are Granger-caused mainly by price changes of grains, live cattle, and wheat, while supply shock granger causes variations mostly in grain prices. We find that, from the point of view of static connectedness, for both, price and volatility spillovers, the livestock is the largest transmitter, while the lean hogs are the major receiver. Our dynamic analysis evidences that connectedness increases during the financial crisis period. Our results are potentially useful for investors, portfolios managers and policy makers.

Gene editing that makes target gene modification in the genome by deletion or addition has revolutionized the era of biomedicine. Clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 emerged as a substantial tool due to its simplicity in use, less cost and extraordinary efficiency than the conventional gene-editing tools, including zinc finger nucleases (ZFNs) and Transcription activator-like effector nucleases (TALENs). However, potential off-target activities are crucial shortcomings in the CRISPR system. Numerous types of approaches have been developed to reduce off-target effects. Here, we review several latest approaches to reduce the off-target effects, including biased or unbiased off-target detection, cytosine or adenine base editors, prime editing, dCas9, Cas9 paired nickase, ribonucleoprotein (RNP) delivery and truncated gRNAs. This review article provides extensive information to cautiously interpret off-target effects to assist the basic and clinical applications in biomedicine.