Practical Guidance Research Articles

A thematic analysis of factors influencing small and medium enterprise adoption of social media marketing: a TOE framework perspective

Purpose This paper aims to examine the factors influencing the adoption of social media marketing by small and medium enterprises (SMEs) in Pakistan. By investigating the drivers and challenges/barriers affecting the adoption of social media marketing tools among SMEs, this study provides practical guidance to SMEs seeking to utilize social media platforms for marketing purposes in a developing context such as Pakistan. Design/methodology/approach Utilizing the Technology-Organization-Environment (TOE) framework as a theoretical framework, qualitative data were collected through semistructured interviews with representatives of SMEs in Pakistan, followed by thematic analysis of the data. Findings The research identifies several key factors influencing the adoption of social media marketing by Pakistani SMEs. These factors include doubts regarding the benefits of social media, alignment with regulatory requirements, challenges related to tracking social media performance, resistance from senior management (older employees), the positive influence of competitive pressure and the Covid-19 pandemic, political instability and increased government taxes on digital services. Stakeholders such as marketing professionals, academics, policymakers, government authorities and SME owners and managers can benefit from these findings. Originality/value This research contributes to the academic literature on the adoption of social media marketing by SMEs, especially within emerging economies. It enriches theoretical understanding of adoption processes and factors, filling gaps in existing knowledge and laying a foundation for future research in this domain. Using the TOE framework, the study reveals that when all factors are adequately considered, SMEs can transition from traditional marketing methods and embrace social media as a digital marketing strategy to enhance performance, profitability, and gain a competitive advantage over their rivals.

Exploring peer-to-peer lending: key influences of firm uncertainty, loan features and venture quality

PurposeThe purpose of this study is to identify the determinants of success in peer-to-peer (P2P) lending campaigns, especially amid global financial disruptions like the COVID-19 pandemic. Addressing a notable gap in current research, we explore how factors such as firm uncertainty, loan characteristics (interest rates and maturity) and venture quality (human, social and intellectual capital) influence P2P lending effectiveness. Using multiple regression analysis on data from 523 projects on the October platform, our study aims to enhance the understanding and operational efficiency of P2P platforms, contributing to a more resilient financial ecosystem.Design/methodology/approachThis study employs a quantitative research design using multiple regression analysis to examine the impact of specific variables on the success of P2P lending campaigns. Data were collected from 523 concluded P2P lending projects on the October platform, spanning from 2015 to 2021. Variables of interest include the level of uncertainty of the firm, loan characteristics such as interest rate and maturity and the quality of the venture assessed through human, social and intellectual capital. This method allows for a robust analysis of the factors contributing to the success of P2P lending within a dynamic financial context.FindingsThe findings of this study reveal that the success of P2P lending campaigns is significantly influenced by the level of uncertainty of the firm, the interest rate of the loan and the quality of the venture. Specifically, higher uncertainty in firms correlates negatively with campaign success, while competitive interest rates positively impact funding outcomes. Furthermore, ventures that demonstrate robust human capital, particularly those with management teams that possess diverse skills and high qualifications, tend to attract more funding. These results underscore the critical role of strategic financial and human resource planning in enhancing the effectiveness of P2P lending platforms.Originality/valueThis study contributes uniquely to the literature by integrating multiple variables – firm uncertainty, loan characteristics and venture quality – into a comprehensive analysis of success factors in P2P lending. It addresses the scarcity of research examining the combined effects of these factors, particularly in the context of global financial disruptions like the COVID-19 pandemic. By focusing on a specific European platform during a dynamic period, this research provides new insights into how P2P lending can adapt to and thrive amid financial crises. The findings offer valuable guidance for both practitioners and policymakers aiming to optimize P2P lending practices in uncertain economic landscapes.

Enterprise Architecture As An Enabler Of Digital Transformation In The Government Sector: Success Factors And Maturity Evaluation Methodology

Enterprise Architecture (EA) plays an important role as an enabler of digital transformation with strategic objectives, especially in digital government initiatives. Despite its potential, EA implementation in the public sector faces challenges such as complex organizational structures, diverse stakeholder interests, and regulatory constraints. This study aims to systematically review the literature to identify critical success factors that influence the success of EA implementation in government and propose a comprehensive maturity evaluation methodology. Using a systematic literature review of 48 studies published between 2018 and 2024, this research identifies key factors such as strategic alignment, governance, human resource capabilities, and stakeholder engagement as critical to achieving effective EA implementation. It also introduces an EA maturity evaluation model designed for the public sector to assess and improve EA practices. The citizen-centric aspect is the novelty of this research where the factors in this aspect characterize the implementation of EA in the digital government sector. The findings provide insights and academic contributions in expanding the study of EA in the public sector as well as providing practical guidance for government agencies to improve their EA maturity so that accelerated digital transformation can be achieved

EGS SO10 - Restructuring of emergency surgical service in DGH leads to significant reduction in time to cholecystectomy for gallstone pancreatitis in line with international guidance

Abstract Background The International Association of Pancreatology guidelines suggest that patients with mild biliary pancreatitis undergo cholecystectomy during their initial hospital admission. A single-center retrospective study was conducted to examine adherence to this guideline following a significant overhaul of emergency surgical services. Our team, with support from the surgical ambulatory emergency care network, revolutionized care through an Emergency Surgery Unit (EmSU) system. This included surgical assessments with ambulation, coordinated radiology appointments, semi-emergency theatre lists twice a week in addition to NCEPOD theatre sessions, and an emergency roster split by patient gender, ensuring a balanced caseload for the surgeons on duty each week. Method A retrospective study of patients with mild biliary pancreatitis for three years before (n = 107) and after (n=108) the EmSU system. Cholecystectomy on index admission was recorded, as was overall time to surgery (days). Data was analysed using GraphPad Prism Version 9.5.1. Data is expressed as Mean ± SEM. Percentages underwent Arcsine transformation prior to inferential analysis. Groups of data were analysed using Students T-Tests. Results The percentage of patients operated on index admission increased 13.1-fold (4.8% to 62.9%; P < 0.01). Days to surgery saw a 10.1-fold reduction (332.5 ± 41.1 to 32.9 ± 6.3 days; P < 0.0001). Conclusion The adoption of our EmSU system has drastically improved care for patients with gallstone pancreatitis, bringing it much closer to best practice guidance. Further improvement is likely with increased buy-in from all members of staff.

Bubble‐Assisted Sample Preparation Techniques for Mass Spectrometry

ABSTRACTThis review delves into the efficacy of utilizing bubbles to extract analytes into the gas phase, offering a faster and greener alternative to traditional sample preparation methods for mass spectrometry. Generating numerous bubbles in liquids rapidly transfers volatile and surface‐active species to the gas phase. Recently, effervescence has found application in chemical laboratories for swiftly extracting volatile organic compounds, facilitating instantaneous analysis. In the so‐called fizzy extraction, liquid matrices are pressurized with gas and then subjected to sudden decompression to induce effervescence. Alternatively, specifically designed effervescent tablets are introduced into the liquid samples. In situ bubble generation has also enhanced dispersion of extractant in microextraction techniques. Furthermore, droplets from bursting bubbles are collected to analyze non‐volatile species. Various methods exist to induce bubbling for sample preparation. The polydispersity of generated bubbles and the limited control of bubble size pose critical challenges in the stability of the bubble–liquid interface and the ability to quantify analytes using bubble‐based sample preparation techniques. This review covers different bubble‐assisted sample preparation methods and gives practical guidance on their implementation in mass spectrometry workflows. Traditional, offline, and online approaches for sample preparation relying on bubbles are discussed. Unconventional bubbling techniques for sample preparation are also covered.

Barriers Hindering the Successful Deployment of GLSS in Organizations: Findings from an Empirical Study

Given the growing interest in manufacturing’s environmental effects, understanding the impact of improvement strategies on sustainability is critical. This study focuses on the implementation of Green Lean Six Sigma (GLSS) in the Mexican manufacturing sector, an area where research is limited, particularly concerning the barriers to successful outcomes. Through the development of a structural equation model using SPSS software,,version 25, 64-bit edition, key barriers such as lack of investment, insufficient participation, ineffective infrastructure, and lack of training were identified as the primary challenges to GLSS implementation. This study also highlights the interrelationships between these barriers and their influence on project success, emphasizing the role of insufficient participation as a critical mediating factor. This insight allows for a deeper understanding of how these obstacles affect the benefits of GLSS initiatives. The findings offer valuable guidance for researchers and practitioners, providing tools to enhance the effectiveness of GLSS implementation in the manufacturing industry. The study’s marginal contribution lies in its identification of key barriers and the introduction of insufficient participation as a mediating factor, offering a more comprehensive understanding of their impact on project success and contributing to improved GLSS adoption strategies.

A data-driven approach to traditional village colors: K-Means clustering of online images

ABSTRACT This study aims to quantify the color characteristics of traditional villages, explore the key aspects of color that attract tourist attention, and propose solutions to enhance the readability and legibility of these villages. The findings are intended to provide practical guidance for the restoration and use of village colors. The research focuses on how tourists perceive the color characteristics of traditional villages. The objective is to conduct color clustering analysis to identify the composition and characteristics of village colors, and further analyze the underlying causes to offer suggestions for optimization and enhancement. It employs a methodology based on urban imagery theory, using clustering and secondary extraction of color data from online images. The results reveal distinct contrasts and harmonies in the colors of the five elements providing a basis for improving spatial readability and visual guidance. These findings not only offer practical design references for optimizing traditional village colors but also provide valuable insights for the protection and restoration of other traditional sites. In particular, the contrast between the colors of boundaries and landmarks can enhance visual recognition, while the complementary color designs of paths and boundaries can improve spatial readability, contributing to the sustainable development of traditional villages.

Empowering Forestry Management and Farmers’ Income Growth Through the Digital Economy—Empirical Evidence from Guizhou Province, China

Facilitating the sustained and stable growth of farmers’ income is crucial for achieving sustainable development in forest regions. As an emerging driving force, the digital economy has demonstrated substantial potential in enhancing farmers’ income and promoting regional economic prosperity in forest areas. Based on survey data from 1043 households across 10 counties in Guizhou Province, China, this study empirically examined the direct and indirect effects of digital economy participation on income growth among farmers in forest regions. The findings revealed that, first, participation in the digital economy significantly contributed to income growth for these households. This effect remained robust across various estimation methods, restricted sample tests, and when replacing dependent variables. Second, forestry management and its diversification played a mediating role in the relationship between digital economy participation and farmers’ income. Participation in the digital economy indirectly influenced income growth by fostering forestry management activities and their diversification. Third, the heterogeneity analysis indicated that digital economy participation had a significant positive impact on the income growth of pure farming households, part-time farming households, and households that had previously escaped poverty. This discovery underscored the unique role of the digital economy in alleviating poverty and preventing its recurrence. The conclusions of this study provide essential theoretical and practical guidance for empowering forestry development through the digital economy and advancing the digital transformation of the forestry industry. More critically, this research presents a novel pathway for the deep integration of the digital economy with forestry, jointly fostering income growth for farmers in forest regions, which holds significant implications for achieving rural sustainable development.

Experimental Study on the Pelleting and Coating Performance of Red Clover Seeds

This study aimed to optimize the pelleting and coating process for red clover seeds, addressing the issue of low pelleting success rates. Through theoretical analysis and experimental research, coating pan fill rate, powder supply quantity, and pelleting time were identified as key factors influencing the pelleting success rate. Single-factor experiments were conducted to investigate the effects of these parameters on the quality of red clover seed pelleting and coating. Based on these results, orthogonal trials were carried out, and response surface analysis was employed to reveal the influence patterns and interactions of each factor. The research results indicate that the factors affecting the pelleting success rate, ranked in order of importance, are coating pan fill rate, pelleting time, and powder supply quantity. Through mathematical model optimization, the optimal combination of process parameters was determined to be coating pan fill rate of 35.9%, powder supply quantity of 160.2 g, and pelleting time of 6.9 s. Under these conditions, a pelleting success rate of 94.3% was achieved in validation experiments. This study provides a theoretical foundation and practical guidance for optimizing the pelleting and coating process of red clover seeds, which is significant for improving seed coating quality and promoting red clover cultivation.

Criminal Regulation of Illegal Use of Citizens’ Personal Information

With the rapid development of information technology, the collection, storage, and use of citizens’ personal information have become increasingly convenient. At the same time, the illegal use of personal information has become rampant, seriously threatening personal privacy rights and social order. This paper aims to systematically explore the criminal regulation of illegal use of citizens’ personal information. It first defines the concept and classification of personal information, then analyzes the specific forms of illegal use of personal information. Through a comparative study of relevant laws and regulations domestically and internationally, it reveals the effectiveness and deficiencies of current criminal regulations in protecting personal information. The research finds that although China has made progress in personal information protection legislation, there are still significant shortcomings in defining criminal liability, clarifying the application of laws, and enforcing regulations. Based on this, the paper proposes several recommendations to improve criminal regulation, including clarifying the constitutive elements of crimes, strengthening law enforcement, enhancing public awareness, and promoting international cooperation, with the aim of providing theoretical support and practical guidance for further improving China’s legal system for personal information protection.

Artificial Intelligence Research in Radiation Oncology: A Practical Guide for the Clinician on Concepts and Methods

Abstract The use of AI holds great promise for radiation oncology, with many applications being reported in the literature, including some of which are already in clinical use. These are mainly in areas where AI provides benefits in efficiency (such as automatic segmentation and treatment planning). Prediction models that directly impact patient decision-making are far less mature in terms of their application in clinical practice. Part of the limited clinical uptake of these models may be explained by the need for broader knowledge, among practising clinicians within the medical community, about the processes of AI development. This lack of understanding could lead to low commitment to AI research, widespread scepticism, and low levels of trust. This attitude towards AI may be further negatively impacted by the perception that deep learning is a “black box” with inherently low transparency. Thus, there is an unmet need to train current and future clinicians in the development and application of AI in medicine. Improving clinicians' AI-related knowledge and skills is necessary to enhance multidisciplinary collaboration between data scientists and physicians, ie, involving a clinician in the loop during AI development. Increased knowledge may also positively affect the acceptance and trust of AI. This paper describes the necessary steps involved in AI research and development, and thus identifies the possibilities, limitations, challenges, and opportunities, as seen from the perspective of a practising radiation oncologist. It offers the clinician with limited knowledge and experience in AI valuable tools to evaluate research papers related to an AI model application.

Accident cause analysis for lifting prefabricated components of assembled buildings based on hybrid simulation technology from human factor perspective

PurposeThis paper aims to explore the characteristics of lifting accidents and the significance of influencing factors and explain the causes from the perspective of human factors, thereby achieving a more accurate understanding of and prevention of lifting accidents.Design/methodology/approachA mixed simulation model for prefabricated component lifting is established by combining discrete event simulation (DES) with the system dynamics (SD) method. In addition, essential parameters and relationships within the system dynamics model are determined through survey questionnaires. Finally, the human factors analysis and classification system (HFACS) is used to analyze the cause of the accident.FindingsThe results show that workers falling from height and workers struck by objects are the most frequent types of lifting accidents. In 2072 experiments, these two types of accidents occurred three and five times, respectively. Besides, the links of “crane movement,” “component binding,” “component placement” and “component unhooking” are particularly prone to lifting accidents. In addition, the completeness of emergency plans, failure to observe the status of the tower crane and lack of safety education and training have emerged as primary influencing factors contributing to the occurrence of lifting accidents.Originality/valueThe findings of the study can serve as a reference basis for practitioners, enabling them to preemptively identify possible risk accidents and adopt corresponding measures to prevent them, ensuring the safety and property of practitioners. Additionally, targeted suggestions and innovative ideas are provided to enhance the safety guarantee of the lifting industry and promote its healthy and stable development through a more concrete theoretical foundation and practical guidance.

Clinical Management of Ovarian Function Suppression in Premenopausal Women With Breast Cancer: A Survey of Members of ASCO

PURPOSE Ovarian function suppression (OFS) with gonadotropin-releasing hormone agonists (GnRHas) is a standard of care for premenopausal patients with high-risk stage II/III hormone receptor–positive breast cancer (BC). Practical guidance on the optimal choice of GnRHa, timing, schedule, and monitoring is limited. Our aim was to determine how oncologists use OFS in routine care. METHODS We designed a questionnaire to determine the choice of GnRHa, schedule, duration, initiation, use of bone modifiers, and monitoring of estradiol (E2). The questionnaire was sent to oncologists treating BC, in practice for >1 year and participating in the ASCO Research Survey Pool (RSP). It was also forwarded by investigators to oncologists meeting these criteria. The survey was open between November 14, 2023, and January 5, 2024. RESULTS Of 996 oncologists participating in the ASCO RSP, 178 (18%) completed the survey. An additional 56 oncologists contacted by investigators responded. Respondents were from the United States (57%), Asia (15%), and Europe (14%). Goserelin (54%) and leuprolide (39%) were the most frequently used GnRHas and were administered once every month by 46%. Approaches to starting GnRHas were varied. Most continued them for the duration of aromatase inhibitor therapy (57%). Estradiol monitoring was performed regularly, sometimes, or never by 43%, 27%, and 27%, respectively. The E2 assays used were standard (65%), ultrasensitive (16%), and unknown (14%). Interpreting E2 assay results were considered difficult by 55%; however, 62% of oncologists changed treatment on the basis of them. A total of 92% of respondents would like ASCO guidance on the practical use of OFS. CONCLUSION Considerable practice variation exists for similar clinical scenarios in OFS administration. Respondents would welcome ASCO guidance on all aspects of OFS.

Video Assisted Learning Module (VALM) for the Least Learned Competencies in General Mathematics

This educational design research aimed to develop and evaluate a video-assisted learning module (VALM) to enhance learners’ mathematics proficiency and improve teachers’ instructional efficiency. The study, anchored on the ADDIE Model, gathered data from year 11 and 12 pupils and five experts. Analysis revealed least-learned competencies in general mathematics, particularly exponential, logarithmic and inverse functions. The VALM comprised a learning module with supplementary video content. The module included a cover page, preface, objectives, study and practice guides, assessment, references, solution boxes, graphing pages and an answer key. The video featured a title, disclaimer, objectives, step-by-step solutions and references. Both learners and experts rated the materials highly acceptable regarding learning objectives, content, organisation, presentation, format, design, activities, and assessment. The VALM was helpful, easy to understand, enjoyable, convenient and mobile. Results suggest that video-assisted learning modules are conducive to enhancing mathematics proficiency and serve as practical supplementary instructional tools across various teaching-learning scenarios in general mathematics.

Virtual communities of practice: nurturing teacher-coordinators’ well-being amidst stress and crisis

PurposeThis longitudinal study investigated the ways in which virtual communities of practice (VCoPs) can support the well-being of teachers in managerial roles during stressful changes and crises. Specifically, it examined the experiences of these educators to better understand how VCoPs contribute to sustaining well-being in the face of challenges.Design/methodology/approachA qualitative study methodology was utilized, consisting of three rounds of interviews with seven teacher-coordinators, coupled with content analysis to discern patterns and insights. A multidimensional model was then applied to pinpoint the associations between the community’s characteristics and the different approaches implemented by these teacher-coordinators to address stress and crises.FindingsThe analysis revealed a range of coping strategies within the VCoPs for handling stress and crises. Participation in virtual spaces was shown to foster in-depth, rich discussions. The multidimensional model captures how social, emotional and cognitive factors can help teacher coordinators navigate challenges.Originality/valueThis study contributes to a broader understanding of the well-being of educational staff, especially in managerial roles, by exploring the subtle dynamics of a VCoP. The findings highlight the impact of the community on teacher-coordinators' well-being in routine, stressful and crisis situations. These insights can provide valuable guidance for educational practitioners and policymakers to enhance the resilience of the education system to diverse challenges.

Examining the components of freedom values in contemporary Chinese society

IntroductionThis research paper delves into the structure and connotation of freedom values within contemporary Chinese society, taking into account the historical, societal, and cultural context.MethodsTo achieve this, a multifaceted approach was adopted, integrating literature analysis, focus group interviews, in-depth interviews, and questionnaire surveys.ResultsThe study culminated in the development of a comprehensive conceptual model comprising five distinct dimensions: behavior within boundaries, independence without interference, autonomy with responsibility, rights with guarantee, and equality without domination.DiscussionThis conceptual model successfully consolidates the prevailing consensus on freedom values among the Chinese populace, offering a robust framework for the propagation and nurturing of freedom within Chinese society. The insights gleaned from this research deepen our comprehension of freedom values and furnish valuable guidance for academics, policymakers, and practitioners keen on advancing freedom and societal well-being.

Abstract 4144549: Proof of Concept of a Novel Culinary Medicine Service Line to Address Diet-Related Cardiovascular Disease Risk Factors

Background: Poor diet has emerged as a top contributor to cardiovascular disease (CVD) in the United States. Evidence-based dietary strategies have been shown to decrease CVD risk by addressing comorbid conditions such as hypertension and diabetes, and there is a growing demand for practical nutrition guidance from health providers. However, implementation of nutrition support in healthcare settings remains limited due to lack of time, expertise, and reimbursement, necessitating creative interprofessional collaboration. Culinary Medicine (CM) combines medical nutrition education with culinary literacy and holds promise to address these challenges. Our study reports on the cascade implementation of a 3-prong CM service line which includes a CM eConsult, 1:1 CM specialty clinic, and shared medical appointment (group visit) in a teaching kitchen at a large, academic medical center from 2021 to 2024. Methods: A CM-specific eConsult was designed and launched on August 1 st 2021 utilizing existing eConsult workflows in the electronic health record. Next, an in-person, interprofessional CM specialty clinic launched at a community-based satellite clinic December 4 th 2022 open to referrals from physicians and patients. In April 2024, established patients in the CM clinic were invited to participate in six, biweekly cooking classes billed as shared medical appointments. A Microsoft PowerBI dashboard was developed to track patient demographics, referrals and participation, associated diagnoses, and billing data for the service line for continuous quality improvement. Results: In the first year of eConsults, 25 eConsults were completed with 19 (76%) reimbursed by insurance. In the first year from launch of the CM specialty clinic, 96 patients completed initial visits with a 100% insurance collections rate. In the recent launch of shared medical appointments, the initial cohort included 17 unique patients with 58% completing at least 4 of 6 classes. Referrals to the CM clinic included hypertension, hyperlipidemia, coronary artery disease, and type 2 diabetes as the top 4 associated diagnoses. Conclusions: We demonstrated proof-of-concept of a novel CM service line as an interprofessional, financially sustainable preventive strategy to target patients with diet-sensitive CVD risk factors such as diabetes, hypertension, and obesity. Future study will investigate the impact on biomarkers of CVD health for patients served by the CM service line.

The evolution of SNAP-Ed: policy, systems and environment (PSE) interventions to enhance nutrition security and health equity in the United States

Purpose This study uses a comprehensive literature review and analysis of recent research, policy documents and program evaluations related to Supplemental Nutrition Assistance Program Education (SNAP-Ed) and policy, systems and environmental (PSE) strategies. Key sources include peer-reviewed articles, the 2025 SNAP-Ed Plan Guidance and case studies of successful PSE interventions. The Social-Ecological Model serves as a framework to organize and analyze the multilevel impacts of PSE interventions. The method involves identifying relevant information, synthesizing key themes and patterns and critically examining the potential impact of PSE strategies on nutrition security and health equity. Design/methodology/approach This paper examines the evolution of the SNAP-Ed from direct nutrition education to a comprehensive approach integrating PSE change strategies. It aims to analyze the rationale, implementation and potential impact of PSE approaches in SNAP-Ed on nutrition security and health equity in the USA. The study explores how these strategies address social determinants of health, promote sustainable population-level changes in nutrition environments, and their capacity to reduce health disparities in low-income communities. It seeks to identify challenges, opportunities and future research directions in implementing PSE strategies within SNAP-Ed. Findings The review reveals that PSE strategies in SNAP-Ed show promise in creating sustainable, population-level changes in nutrition environments and health outcomes. Successful examples, such as healthy corner store initiatives and workplace wellness programs, demonstrate the potential of PSE approaches to improve access to healthy food options and physical activity opportunities. The integration of PSE strategies has enhanced SNAP-Ed’s capacity to address social determinants of health and promote health equity. However, challenges including resource constraints, political opposition and the need for cross-sector collaboration persist. The effectiveness of PSE interventions relies heavily on community engagement, partnerships and supportive policies. Practical implications The findings underscore the importance of adopting comprehensive, multilevel approaches in nutrition education and obesity prevention programs. For SNAP-Ed implementers, this implies a need to develop expertise in PSE strategies, foster cross-sector partnerships and engage communities in intervention design and implementation. Policymakers should consider increasing support and resources for PSE approaches within SNAP-Ed and similar programs. Public health practitioners can use these insights to design more effective, equitable interventions that address root causes of nutrition insecurity. The study also highlights the need for improved evaluation methods to assess the long-term impact of PSE strategies on population health outcomes. Social implications This study highlights the importance of addressing social determinants of health, such as poverty and access to healthy food options, to promote equitable health outcomes. It underscores the potential of community-driven, multilevel interventions in building a more just and equitable food system accessible to all. Originality/value This paper provides a comprehensive analysis of the shift toward PSE strategies in SNAP-Ed, offering valuable insights into the program’s evolution and its potential to address complex public health challenges. By examining both successes and challenges, it contributes to the growing body of evidence on the effectiveness of multilevel interventions in promoting nutrition security and health equity. The study’s emphasis on the role of community engagement and partnerships in PSE implementation offers practical guidance for program planners and policymakers.

Analysis of the Causes and Configuration Paths of Explosion Accidents in Chemical Companies Based on the REASON Model

Explosion accidents, representing one of the most severe accident types within the chemical industry, pose substantial threats to personnel safety, economic losses, and environmental pollution, among other consequences. This paper constructs a research framework based on the REASON theory, utilizing accident investigation reports of 30 typical chemical enterprise explosion accidents in China from 2013–2022 as research samples. The fsQCA method is employed to deeply explore the influencing factors and causal configuration pathways of chemical explosion accidents from a configurational perspective. The study findings indicate that the occurrence of explosions in chemical enterprises is the result of the coupled effects of multiple factors, with five complex accident causation configurations, which can be summarized into the following three categories: organizational management deficiencies, supervision deficiencies, and behavior–risk linkages. Organizational management and safety supervision have a direct and significant impact on the occurrence of explosions in chemical enterprises and are key factors in the accidents. The research conclusions contribute to a rational understanding of the complex causes of explosions in chemical enterprises and provide practical guidance for the prevention and control of such accidents.

From hype to strategy: navigating the reality of experimental strategic adoption of AI technologies in libraries

PurposeThe article highlights the value of adopting an experimental strategy for artificial intelligence (AI) adoption in libraries, with a specific focus on the University of Toronto (UofT) libraries as a case study. The experimental approach entails carrying out small-scale, effective, quick, and reversible experiments to increase awareness, reduce risks with adoption of incorrect, ineffective, or full-scale adoption; increase flexibility in adopting new technologies in the rapidly evolving AI industry; and increase open-mindedness to consider diverse perspectives even though they go against one’s held perceptions, and develop dynamic capabilities to innovate. To fully realize the revolutionary potential of AI technologies in libraries, it is crucial to adopt new technologies strategically, driven by experimentation, collaboration, and knowledge sharing.Design/methodology/approachMixed-model research involving case study of UofT libraries and the author’s professional experiences in digitally transforming libraries is used to answer the research question. AI is an emerging area and hence its applications in libraries. Leveraging the author’s professional and research expertise, the findings from the case study are enriched, offering broader perspectives and more nuanced implications.FindingsLibraries can recognize emerging opportunities, adapt to the shifting AI landscape, and effectively exploit AI technologies because of the development of dynamic capabilities and a focus on innovation. The UofT instance sheds light on the experimental strategy and acts as a lens to comprehend how to strategically think about the complete AI spectrum rather than keeping an eye on a few technologies that otherwise might just be overhyped in media outlets. A mix of centralization and decentralization of AI technology adoption experimentation is evident at UOT, where any librarian is free to test out a new tool and share their findings with their peers in the expectation that other libraries will embrace it as well. The reverse scenario is also conceivable (top management to individual libraries). UofT’s culture fosters collaboration and knowledge-sharing among librarians, promoting experimentation and innovation. Cocreation with patrons, including student entrepreneurs, enhances dynamic capabilities and informs rational adoption decisions. Looking at the results, some future research directions emerge that could strengthen the library’s focus on AI. The future research directions indicate the need for further investigation into experiment design, particularly focusing on experimentation policies, monitoring and evaluation of experimentation activities, and fostering greater collaboration with patrons. Additionally, exploring AI adoption factors at both organizational and individual levels is essential to create a supportive environment for these experiments. Conducting continuous AI experiments enables librarians to critically assess AI technologies by leveraging their experiences with various applications, allowing them to distinguish practical solutions from market hype and concentrate on options that truly enhance their library operations.Practical implicationsThe article contributes to the knowledge of strategic AI technology adoption and the role of experimentation in libraries’ adoption of AI technologies. This paper offers practical guidance for libraries of all sizes and resource levels seeking to experiment with AI technologies. It encourages the creation of a collaborative environment where patrons and peers can come together to experiment and share knowledge. Additionally, it encourages libraries to explore various research directions—such as defining experimentation policies, integrating monitoring and evaluation (M&E) to assess the effectiveness of experiments, fostering collaboration, and leveraging AI adoption factors—to cultivate a culture of experimentation. This approach aims to increase the number of experiments and, consequently, the adoption of valuable AI technologies.Originality/valueAI in libraries is rapidly evolving, but current literature remains underdeveloped and lacks comprehensive adoption frameworks. Investigating individual libraries’ AI practices and sharing these insights will enable collaborative learning, helping them improve overall adoption process, fostering further innovation with emerging technologies, and helping in development of a theoretical foundation or maturity of AI domain. The research outcomes hold significant value for a wide range of libraries, from those hesitant to adopt AI due to ethical concerns to those actively experimenting with AI technologies. The article uniquely recommends further research at the intersection of library AI-driven digital transformations, cocreation, monitoring and evaluation (M&E), adoption models, and AI experimentation policies that ethically balances library innovation focus and data privacies.