bluuebunny/crossref_metadata_2025_split huggingface dataset:
Relationship between pesticide research output and GDP: a socio-economic analysis
Authors: Murugappan Sivagami , Ramalingam Jeyshankar 
Published: February 2024

Purpose
The focus of this study was to evaluate the relationship between research publications in the pesticide field, a country’s gross domestic product (GDP) and GDP per capita. The study aims to analyze pesticide use in association with a country’s population and research publications. The purpose of this study is to uncover the country’s contribution to pesticide research and assess the financial resources allocated to it as a percentage of their GDP by exploring these factors.

Design/methodology/approach
The Web of Science database was used to retrieve data for the period of 2001–2020. The use of scientometric indicators allowed for the analysis of the collaborative patterns and active performance of countries in pesticide research. Socio-economic analysis was used to determine the contribution of countries toward pesticide research.

Findings
This study demonstrated a strong association (0.952%) between a country’s GDP and its research publications in the field of pesticide research. Countries, such as Denmark, Belgium and Australia, have benefited from global collaboration, which has enhanced their research efforts. Despite ranking lower in pesticide utilization, India focused on pesticide research, as indicated by its high publication/GDP per capita ratio (0.26).

Originality/value
Research on pesticides directly impacts agricultural practices, which, in turn, influence the economic production of the agricultural sector. Changes in pesticide usage can have inference for crop yields, food price and, eventually, the GDP. Comparative analysis can assist in evaluating the efficiency of regulatory policies in balancing ecological concerns with economic interests. Changes in regulations may impact both pesticide usage and economic outcomes.
Storm in a teacup: implications of mobile phone literacy on sustainable smallholder agri-food supply chains in developing economies
Authors: Fernando W. Madushan , Perera H. Niles , Ratnayake R.M. Chandima , Thibbotuwawa Amila 
Published: February 2024

PurposeThis study explores digital transformation in the tea supply chain within developing economies, with a focus on smallholder tea producers in Sri Lanka. Tea is one of the most widely consumed beverages in the world. Among the tea producers, smallholder tea producers account for a substantial portion of total tea production in several countries. Mobile phones play a significant role in providing smallholder producers with access to crucial agricultural information, markets and financial services.Design/methodology/approachThis study adopts a deductive approach, analysing mobile phone ownership, literacy, experience and perception among smallholder tea producers. The chi-squared test of independence and hierarchical clustering methods were used to test the hypotheses and address the research questions.FindingsThe study identifies four clusters of smallholder tea producers as Basic Tech Adopters, Digital Laggards, Skeptical Feature Phone Users and Tech-savvy Adopters based on their characteristics towards mobile-based technologies. Approximately 75% of the surveyed sample, which included both tech-savvy and basic-tech adopters, showed a positive attitude toward adopting mobile-based agricultural technologies.Practical implicationsThe study suggests developing targeted strategies and policies to enhance the productivity of the smallholder tea production process in developing economies. The study highlights the importance of awareness, access, affordability and availability when implementing digital services for businesses at the base of the pyramid, such as tea smallholdings in developing economies.Originality/valueThe present study aims to address the lack of data-driven empirical studies on the use of mobile phones in smallholder settings. The findings of this study enable the enhancement of entrepreneurship within the tea production supply chain, especially, within stakeholders who deliver digital transformation support services.
Sustainable HRM the next hotspot for management research? A study using topic modelling
Authors: Singh Shefali , Awasthi Kanchan , Patra Pradipta , Srivastava Jaya , Trivedi Shrawan Kumar 
Published: February 2024

Purpose
Sustainable human resource management (SuHRM), which aims to achieve positive environmental, social and economic outcomes at the same time, has gained prominence across industries. However, the challenges of implementing SuHRM across industries are largely under-studied. The purpose of this study is to identify the grey areas in the field of SuHRM by using an unsupervised learning algorithm on the abstracts of 607 papers published in prominent journals from 1995 to 2023. Most of the articles have been published post-2018.

Design/methodology/approach
The analysis of the data (abstracts of the selected articles) has been done using topic modelling via latent Dirichlet algorithm (LDA).

Findings
The output from topic modelling-LDA reveals nine primary focus areas of SuHRM research – the link between SuHRM and employee well-being; job satisfaction; challenges of implementing SuHRM; exploring new horizons in SuHRM; reaping the benefits of using SuHRM as a strategic tool; green HRM practices; link between SuHRM and organisational performance; link between corporate social responsible and HRM.

Research limitations/implications
The insights gained from this study along with the discussions on each topic will be extremely beneficial for researchers, academicians, journal editors and practitioners to channelise their research focus. No other study has used a smart algorithm to identify the research clusters of SuHRM.

Originality/value
By utilizing topic modeling techniques, the study offers a novel approach to analyzing and understanding trends and patterns in HRM research related to sustainability. The significance of the paper would be in its potential to shed light on emerging areas of interest and provide valuable implications for future research and practice in Sustainable HRM.
The persuasion of performative technologies: constructing calculating selves in universities
Authors: Funck Elin K. , Kallio Kirsi-Mari , Kallio Tomi J. 
Published: February 2024

Purpose
This paper aims to investigate the process by which performative technologies (PTs), in this case accreditation work in a business school, take form and how humans engage in making up such practices. It studies how academics come to accept and even identify with the quantitative representations of themselves in a translation process.

Design/methodology/approach
The research involved a longitudinal, self-ethnographic case study that followed the accreditation process of one Nordic business school from 2015 to 2021.

Findings
The findings show how the PT pushed for different engagements in various phases of the translation process. Early in the translation process, the PT promoted engagement because of self-realization and the ability for academics to proactively influence the prospective competitive milieu. However, as academic qualities became fabricated into numbers, the PT was able to request compliance, but also to induce self-reflection and self-discipline by forcing academics to compare themselves to set qualities and measures.

Originality/value
The paper advances the field by linking five phases of the translation process, problematization, fabrication, materialization, commensuration and stabilization, to a discussion of why academics come to accept and identify with the quantitative representations of themselves. The results highlight that the materialization phase appears to be the critical point at which calculative practices become persuasive and start influencing academics’ thoughts and actions.
Estimation of an attribute value peer-to-peer accommodation platform using a choice experiment: focus on Airbnb
Authors: Jung Jiwoo , Lee Won Seok , Moon Joonho 
Published: February 2024

Purpose
The purpose of this study is to identify individuals’ preferences for the information attributes of Airbnb, a representative peer-to-peer (P2P) accommodation platform. In the sharing economy, platforms are considered to be the principal intermediaries in supply and demand, and these platforms have distinctly different attributes from traditional accommodation reservation systems.

Design/methodology/approach
The present study used a choice experiment, which is a method for systematically identifying attributes’ preferences in the form of marginal willingness-to-pay (MWTP). Amazon Mechanical Turk, a crowdsourcing marketplace, was used for data collection, and 243 respondents ultimately participated in the survey.

Findings
Results showed that respondents’ choices were positively affected by the number of pictures of an accommodation, host experience, cancellation policy and local information but negatively affected by cost. Regarding MWTPs, host experience had the highest value (US$84.25), followed by cancellation policy (US$40), photos (US$26.67) and local information (US$10.92).

Originality/value
These study results could provide strategic guidance for guiding the development of P2P accommodation platforms by providing a prioritized list of preferred attributes for Airbnb.
Executive team risk appetite, financial development and re-innovation strategy after enterprise innovation failure: evidence from China
Authors: Zhang Yang , Zhou Wentao , Pan Xiaoyao 
Published: February 2024

PurposeThis article empirically tests the impact of risk appetite of the executive team on the re-innovation strategy after technological innovation failure using a panel regression model from the perspective of regional financial development level of enterprises.Design/methodology/approachBy means of time series global principal component analysis and panel regression model method, the study validated and analyzed the impact of risk appetite of the executive team on the re-innovation strategy after enterprise technological innovation failure.FindingsThe research found that the higher the risk appetite of executive team, the more inclined the enterprise is to choose the “focusing on quantity, ignoring quality” re-innovation strategy after technological innovation failure. The better the financial development level of the region where the enterprise is located, the better it can effectively reduce the re-innovation strategy of “focusing on quantity, ignoring quality” of the enterprise due to the high risk appetite of the executive team.Originality/valueThe findings of this study are helpful in improving the financial development level of the region where the enterprise is located. It can help the executive team of the enterprise to more objectively choose the innovation strategy after technological innovation failure, and reduce the phenomenon that the executive team of the enterprise only pays attention to the quantity of re-innovation and underestimates the quality of re-innovation after technological innovation failure due to its high risk appetite.
The association of Healthy Eating Index and its components with levels of fasting blood sugar and lipid profile in normoglycemic and hyperglycemic individuals
Authors: Moradiani Mohammad , Movahedi Ariyo , Djazayery Abolghassem 
Published: February 2024

Purpose
This study aims to assess the association of Healthy Eating Index (HEI) with levels of fasting blood sugar (FBS) and lipid profile in normoglycemic and elevated FBS patients.

Design/methodology/approach
This case-control study was conducted on 144 participants, namely, 72 normoglycemic subjects (FBS < 100 mg/dl) and 72 high-glycemic patients (FBS ≥ 100 mg/dl) aged 20–60 years of age, who were selected from the nutrition and diet clinics in Tehran city. The dietary intake was collected by using a validated food frequency questionnaire to determine the HEI score.

Findings
The mean±SD age and body mass index of participants were 47.1 ± 12.7 years and 29.6 ± 6.0 kg/m2, respectively. The median (interquartile range) of HEI scores in the normoglycemic group and the high-glycemia group were 19.34 (15.24–24.31) and 16.53 (13.35–24.07), respectively. In the overall population, the findings of the multi-variable linear regression model indicated a positive association between the HEI score and high-density lipoprotein-cholesterol (HDL-C) (ß = 0.34; 95%CI: 0.05–0.64, P = 0.01). However, there is no significant association between HEI and HDL-C in normoglycemic (ß = 0.19; 95%CI: −0.31, 0.69, P = 0.45) and hyperglycemic subjects (ß = 0.28; 95%CI: −0.10–0.66, P = 0.15). Furthermore, the association of HEI with levels of FBS, triglycerides (TGs) and low-density lipoprotein-cholesterol (LDL-C) was not significant in any of the analyzed groups, including the total population, normoglycemic individuals and hyperglycemic subjects.

Originality/value
This study was the first study to assess the role of HEI and its components with levels of FBS and lipid profile in normoglycemic and hyperglycemic individuals in Iran. The findings suggested that higher adherence to HEI may be associated with an increase in the HDL-C level. However, HEI could not predict FBS, TGs and LDL-C levels in the adult population.
Fabrication of cathode composite Co3O4/CC and study on electrochemical properties of zinc cobalt battery
Authors: Tan Wenhai , Zhang Yichen , Song Yuhao , Ma Yanbo , Zhao Chao , Zhang Youfeng 
Published: February 2024

Purpose
Aqueous zinc-ion battery has broad application prospects in smart grid energy storage, power tools and other fields. Co3O4 is one of the ideal cathode materials for water zinc-ion batteries due to their high theoretical capacity, simple synthesis, low cost and environmental friendliness. Many studies were concentrated on the synthesis, design and doping of cathodes, but the effect of process parameters on morphology and performance was rarely reported.

Design/methodology/approach
Herein, Co3O4 cathode material based on carbon cloth (Co3O4/CC) was prepared by different temperatures hydrothermal synthesis method. The temperatures of hydrothermal reaction are 100°C, 120°C, 130°C and 140°C, respectively. The influence of temperatures on the microstructures of the cathodes and electrochemical performance of zinc ion batteries were investigated by X-ray diffraction analysis, scanning electron microscopy, cyclic voltammetry curve, electrochemical charging and discharging behavior and electrochemical impedance spectroscopy test.

Findings
The results show that the Co3O4/CC material synthesized at 120°C has good performance. Co3O4/CC nanowire has a uniform distribution, regular surface and small size on carbon cloth. The zinc-ion battery has excellent rate performance and low reaction resistance. In the voltage range of 0.01–2.2 V, when the current density is 1 A/g, the specific capacity of the battery is 108.2 mAh/g for the first discharge and the specific capacity of the battery is 142.6 mAh/g after 60 charge and discharge cycles.

Originality/value
The study aims to investigate the effect of process parameters on the performance of zinc-ion batteries systematically and optimized applicable reaction temperature.
Optimization and modelling of WCEDM process parameters for GZR-AA7475 HMMC using GRA and Taguchi approach
Authors: Singuru Madhavarao , V.V.S. Kesava Rao , Chekuri Rama Bhadri Raju 
Published: February 2024

Purpose
This study aims to investigate the optimal process parameters of the wire-cut electrical discharge machining (WCEDM) for the machining of the GZR-AA7475 hybrid metal matrix composite (HMMC). HMMCs are prepared with 2 Wt.% graphite and 4 Wt.% zirconium dioxide reinforced with aluminium alloy 7475 (GZR-AA7475) composite by using the stir casting method. The objective is to enhance the mechanical properties of the material while preserving its unique features. WCEDM with a 0.18 mm molybdenum wire electrode is used for machining the composite.

Design/methodology/approach
To conduct experimental studies, a Taguchi L27 orthogonal array was adopted. Input variables such as peak current (Ip), pulse-on-time (TON) and flushing pressure (PF) were used. The effect of process parameters on the output responses, such as material removal rate (MRR), surface roughness rate (SRR) and wire wear ratio (WWR), were investigated. The grey relational analysis (GRA) is used to obtain the optimal combination of the process parameters. Analysis of variance (ANOVA) was also used to identify the significant process parameters affecting the output responses.

Findings
Results from the current study concluded that the optimal condition for grey relational grade is obtained at TON = 105 µs, Ip = 100 A and PF = 90 kg/cm2. Peak current is the most prominent parameter influencing the MRR, whereas SRR and WRR are highly influenced by flushing pressure.

Originality/value
Identifying the optimal process parameters in WCEDM for machining of GZR-AA7475 HMMC. ANOVA and GRA are used to obtain the optimal combination of the process parameters.
Deaf and hard‐of‐hearing EFL learners' perception of learning English: A narrative inquiry
Authors: Rezvani Reza , Ghanbar Hessameddin , PourhematKhanshir Yasamin 
Published: February 2024

AbstractThere is limited research on deaf and hard‐of‐hearing (D/HH) learners' learning English as a foreign language. It is even more scant in contexts such as Iran where D/HH learners are least visible and represented. This narrative inquiry aimed to explore Iranian D/HH English as a foreign language (EFL) learners' lived experience in learning English. The data were collected through semi‐structured interviews with 10 undergraduate students of English. The data were thematically analysed, yielding five themes: (1) learning English and its relevance to personal goals and aspirations; (2) perceived language‐related difficulties; (3) awareness of the differences in their language learning experience as D/HH learners; (4) significance of visual communication for D/HH learners of English; and (5) the role and support of technology. These themes provided a multidimensional understanding of these learners' perception of their foreign language learning trajectory. The results of this study have implications for various stakeholders in the context of special needs language education.
TOXIC FORMATIONS: Race, Place and the Politics of Pollution on the Banks of the Ganga
Authors: Ponnaganti Amani 
Published: February 2024

AbstractPollution in the environment emerges as a legal and technical object on the one hand, and as a repository of social and cultural beliefs on the other. What happens when we trouble the idea that these belong to different domains and think about seemingly divergent meanings of pollution together? In this article, I draw from anti‐caste and anti‐racist work to explore this question. Extending critical urban scholarship on environmental politics, I attend to formations of caste and religion alongside judicial and political discourse on preventing pollution to the river Ganga in North India. In our present moment, on the banks of the sacred river, extremist leaders mobilize regulations to target minoritized Muslim and Dalit communities in Kanpur's leather industry. I argue that the roots of these actions lie in an environmental petition from the mid‐1980s which transformed urban environmental governance in North India, as the court decoupled questions of environmental protection from economic and social justice. I suggest that the analytic of regional racial formations helps us grapple with uneven socio‐spatial landscapes in postcolonial cities and sharpens our understanding of environmental injustices by moving beyond fixed categories of difference.
Exploring the learning experiences of neurodivergent college students inSTEMcourses
Authors: Wang Karen D. , McCool Jake , Wieman Carl 
Published: February 2024

AbstractNeurodivergent students exhibit an inclination towards Science, Technology, Engineering and Mathematics (STEM) fields, yet their learning experiences in STEM courses remain underexamined. Utilizing an online survey of neurodivergent (n = 60) and neurotypical (n = 83) US college students, this study identified various factors influencing their self‐perceived learning experiences, including interest in the course content, instruction quality and performance outcomes. Compared to their neurotypical peers, neurodivergent students attributed negative experiences in STEM courses less frequently to performance‐related factors and more often to a mismatch between their interests and the course content. Both groups also articulated a variety of strengths and challenges encountered in their STEM studies. Neurodivergent students were more likely to report having interest and passion for STEM and less likely to report having peer support and effective study skills and habits as their primary strength for studying STEM. Conversely, while neurotypical students cited difficult content as their central challenge, neurodivergent students more commonly faced challenges with focus and attention. Despite the study's limited sample size, it revealed emerging patterns that emphasize the importance of developing inclusive teaching methods and specific support mechanisms to cater to the unique strengths and challenges of neurodivergent students in higher education.
Connectivity conservation planning through deep reinforcement learning
Authors: Equihua Julián , Beckmann Michael , Seppelt Ralf 
Published: February 2024

AbstractThe United Nations has declared 2021–2030 the decade on ecosystem restoration with the aim of preventing, stopping and reversing the degradation of the ecosystems of the world, often caused by the fragmentation of natural landscapes. Human activities separate and surround habitats, making them too small to sustain viable animal populations or too far apart to enable foraging and gene flow. Despite the need for strategies to solve fragmentation, it remains unclear how to efficiently reconnect nature. In this paper, we illustrate the potential of deep reinforcement learning (DRL) to tackle the spatial optimisation aspect of connectivity conservation planning.The propensity of spatial optimisation problems to explode in complexity depending on the number of input variables and their states is and will continue to be one of its most serious obstacles. DRL is an emerging class of methods focused on training deep neural networks to solve decision‐making tasks and has been used to learn good heuristics for complex optimisation problems. While the potential of DRL to optimise conservation decisions seems huge, only few examples of its application exist.We applied DRL to two real‐world raster datasets in a connectivity planning setting, targeting graph‐based connectivity indices for optimisation. We show that DRL converges to the known optimums in a small example where the objective is the overall improvement of the Integral Index of Connectivity and the only constraint is the budget. We also show that DRL approximates high‐quality solutions on a large example with additional cost and spatial configuration constraints where the more complex Probability of Connectivity Index is targeted. To the best of our knowledge, there is no software that can target this index for optimisation on raster data of this size.DRL can be used to approximate good solutions in complex spatial optimisation problems even when the conservation feature is non‐linear like graph‐based indices. Furthermore, our methodology decouples the optimisation process and the index calculation, so it can potentially target any other conservation feature implemented in current or future software.