bluuebunny/crossref_metadata_2025_split huggingface dataset:
Process supply chain integration: construct development and model testing
Authors: Robinson Jessica , Ralston Peter 
Published: June 2024

PurposeThis research offers clarity regarding process supply chain integration through two deliverables: (1) developing six constructs (both integrative mechanisms and integrative practices for internal, customer, and supplier integration); and (2) empirically testing a theoretically grounded supply chain process model using three distinct datasets (internal, customer, and supplier integration).Design/methodology/approachThe construct development procedure involved a continuous improvement cycle for identifying 1,450 items previously used to measure internal, customer, and/or supplier integration constructs; classifying the items into one of six categories; and refining the instruments based on pilot data and peer feedback. Three surveys (targeted key informants based on their specialized knowledge on internal, customer, or supplier integration) were disseminated for evaluating the measurement instruments and testing the theoretically grounded supply chain management process models, by performing the Covariance-Based Structural Equation Modeling (CB-SEM) analysis technique.FindingsThe findings revealed consistencies across all three dimensions of supply chain integration where integrative mechanisms and integrative practices are distinct constructs; integrative mechanisms make it possible for integrative practices and supply chain orientation to occur in a supply chain company; and integrative practices and supply chain orientation improve business performance.Originality/valueOur study contributes to answering how process-oriented supply chain management occurs, responding to calls for research in the supply chain management discipline and advancing theory development around supply chain integration. The theoretical and managerial contributions of developing six constructs and testing three supply chain management process models relate to identifying the specific aspects of supply chain integration that improves business performance. The three tested models also reveal both direct and mediating effects of integrative practices and supply chain orientation, which contributes to the practical understanding of effective supply chain management implementation.
Broad and alien is the field: dependence and heterogeneity in management research practices in Latin America
Authors: Manky Omar , López Nattaly 
Published: June 2024

Purpose
This study aims to explore the ways in which management scholars affiliated with Peruvian universities navigate the tensions between global expectations and local realities in their research practices, drawing on their capitals and habitus.

Design/methodology/approach
Drawing on Bourdieu’s field theory, the authors analyse 25 in-depth interviews and a unique database of academic publications in the business and management field from 2000 to 2022. The analysis identifies the positions scholars occupy within the Peruvian management field and examines the factors influencing their research practices.

Findings
The authors find that the Peruvian management field is complex and unequal, where actors have different positions and interests, but are all influenced by a logic of academic dependency on the Global North. The authors identify three main positions held by scholars: transnational dominators, who accumulate greater resources and ignore local debates; dominated adaptors, who unsuccessfully try to imitate the dominant logic; and isolated innovators, who critique the dominant model but lack institutional support to develop alternatives.

Originality/value
This research presents an analysis of the Peruvian management field, a site often overlooked in international business studies. By examining scholarly practices, the authors reveal how academic inequalities are reproduced by the forces of globalization. The study underscores the urgent need for greater acknowledgement of regionally informed research, advocating for a more inclusive and diverse understanding in the field of management research.
The role of artificial intelligence (AI) in improving technical and managerial cybersecurity tasks’ efficiency
Authors: Gafni Ruti , Levy Yair 
Published: June 2024

Purpose
Artificial intelligence (AI) can assist in the worldwide shortage of cybersecurity workers in technical and managerial roles. Thus, the purpose of this study was to investigate the role of AI in automating many of the routine tasks associated with cybersecurity. As such, AI enables cybersecurity personnel to reduce their workloads and focus on more strategic aspects of their work.

Design/methodology/approach
This study is an exploratory field study. The authors started by conducting a literature review to assess the possibility that AI tools can provide and how they can improve cybersecurity efficacy. Following this, the authors identified the specific core tasks for two cybersecurity work roles (technical and managerial) and searched for specific commercial tools that can perform each of the tasks. Then, the authors used the free ChatGPT 3.5 to list the current cybersecurity systems that use AI for the associated tasks, which the authors then reviewed with the tools’ documentation and websites to confirm these tasks were conducted or assisted by AI.

Findings
Results indicated that all 14 cybersecurity tasks of the technical work role are currently noted to be performed by commercial cybersecurity systems with AI-integrated capabilities, while only 11 of the 17 managerial work role tasks currently appear to be performed by AI.

Practical implications
The rapid integration of AI capabilities into commercial cybersecurity systems may suggest that the cybersecurity workforce must be currently trained on how to use AI tools in their daily operations, especially as it pertains to technical cybersecurity work roles.

Social implications
The cybersecurity workforce shortage is reported to exceed four million cybersecurity workers worldwide in 2023. Thus, further understanding of the role of AI in improving the efficiency of technical and managerial cybersecurity tasks is significant.

Originality/value
The value of this research lies in the initial assessment of the current AI capabilities of commercial cybersecurity systems, which will ultimately provide the “super-human” performances resulting from human-AI teaming.
Can AI robots foster social inclusion? Exploring the role of immersive augmentation in hospitality
Authors: Gonzalez-Jimenez Hector , Costa Pinto Diego 
Published: June 2024

Purpose
Grounded on the X Reality framework and human–machine collaboration, this study aims to explore the potential of immersive augmentation through artificial intelligence (AI) service robots for promoting social inclusion in the hospitality industry.

Design/methodology/approach
Three experimental studies across diverse hospitality contexts examine the effects of immersive augmentation using inclusive-AI service robots compared to standard-AI robots. The studies also uncover the underlying process of perceived ethicality and the moderating role of customers’ familiarity with AI.

Findings
The results indicate that immersive augmentation through inclusive-AI service robots generates higher levels of supportive tipping behavior (Studies 1 and 3), superior buying intentions (Study 2) and an increased likelihood for customers to pay a premium price (Study 2). These effects are mediated by perceived ethicality (Studies 1–3). However, the impact of immersive augmentation for social inclusion is contingent upon customers’ familiarity with AI: customers with high familiarity with AI exhibit lower levels of supportive tipping behavior (Study 3).

Research limitations/implications
The findings emphasize the importance of perceived ethicality and customers’ familiarity with AI in determining the effectiveness of immersive augmentation for social inclusion in hospitality.

Originality/value
This study contributes to the literature by exploring the potential of immersive augmentation using AI service robots for social inclusion in hospitality. It offers novel insights by highlighting the importance of perceived ethicality and customers’ familiarity with AI. The findings provide valuable guidance for hospitality managers seeking to leverage AI technology to foster social inclusion.
Managerial sentiment, life cycle and corporate investment: a large language model approach
Authors: Rana Anamika , Sahu Asis Kumar , Debata Byomakesh 
Published: June 2024

PurposeThis paper investigates the relationship between managerial sentiment and corporate investment in emerging capital markets. Further, we begin with the assertion that the positive impact of managerial sentiment on corporate investment varies according to the corporate life cycle. Lastly, we investigate whether the relationship between managerial sentiment and corporate investment can be moderated by factors like (1) economic policy uncertainty/geo-political risk, (2) size of the firm, (3) financial constraint, (4) industrial competition, and (5) Environmental Social and Governance (ESG) rating.Design/methodology/approachThis study has considered Indian listed companies (465 firms) for the period spanning from 2003–2004 to 2022–2023. This study constructs the managerial sentiment using a novel large language model-financial bidirectional encoder representation from the Transformers (FinBERT), as well as on management discussion and analysis reports. Then, we employ fixed effect regression to investigate the relationship between managerial sentiment and corporate investment. Additionally, we use propensity score matching, two-stage least squares instrumental variables, and a two-step system generalized method of moments approach for robustness tests.FindingsThe findings show a positive and significant relationship between managerial sentiment and corporate investment. Additionally, our results demonstrate that this relationship is evident only during the growth and maturity phase of the corporate life cycle. Moreover, uncertainty pertaining to the economy and geopolitical issues, firm size, financial health, industry dynamics, and ESG disclosure also play a crucial role in shaping the investment-sentiment relationship.Originality/valueThe study is unique because it determines the relationship between managerial sentiment and corporate investment by using the novel FinBERT model. In addition, we have introduced a corporate life cycle, which is an essential aspect of our study. Additionally, this research was conducted in an emerging market with more information asymmetry and weaker disclosure rules. Thus, other emerging markets can benchmark the outcomes.
Teaching and testing in the era of text-generative AI: exploring the needs of students and teachers
Authors: Jochim Julia , Lenz-Kesekamp Vera Kristina 
Published: June 2024

Purpose
Large language models such as ChatGPT are a challenge to academic principles, calling into question well-established practices, teaching and exam formats. This study aims to explore the adaptation process regarding text-generative artificial intelligence (AI) of students and teachers in higher education and to identify needs for change.

Design/methodology/approach
The issue is explored in a mixed-methods approach based on Domestication Theory (Silverstone et al., 1992; Silverstone, 1994), incorporating views of both teaching staff and students. Both statistical and content analyses were carried out.

Findings
The results show that both students and teachers are conflicted about generative AI and its usage. Trepidation and fear stand against a general feeling that AI is an integral part of the future and needs to be embraced. Both groups show marked needs for training and rules and offer a variety of ideas for new exam formats.

Originality/value
This study provides a unique insight by exploring the attitudes and usage intentions regarding generative AI of two stakeholder groups: students and teachers. Its results can be of significant use to institutions deciding on their strategy regarding AI. It illustrates attitudes and usage intentions as well as needs of both groups. In addition, ideas for new assessment and teaching formats were generated.
Co-designing with library stakeholders: building a national virtual library
Authors: Lee Chae Yeon , Lee Kung Jin 
Published: June 2024

PurposeThis paper states the application of co-design methods in building a national virtual library in a metaverse environment with an interest in digital transformation.Design/methodology/approachA case study of a national digital library and data obtained through a co-design approach is applied.FindingsThe study findings demonstrate the usage of the co-design approach in incorporating the different stances of the library stakeholders and discuss the potential services that can be transferred to a digital infrastructure.Originality/valueThis study contributes by sharing methodological insights on applying co-design methods to build a national virtual library with different library stakeholders. The study also shares empirical findings on the insights and practical recommendations for building a national metaverse library that reflects the needs and aspirations of its stakeholders.
Association between lifeline diet score (LLDS) and polycystic ovary syndrome (PCOS): case-control study
Authors: Fateh Hawal Lateef , Rashid Sameeah Abdulrahman 
Published: June 2024

Purpose
Polycystic ovary syndrome (PCOS) is a prevalent and multifaceted metabolic and endocrine disorder that affects a significant number of women in their reproductive years. The purpose of this study is to investigate the relationship between the lifeline diet score (LLDS) and PCOS.

Design/methodology/approach
In this study, the authors enrolled 105 women who had recently been diagnosed with PCOS. 105 women without PCOS, matched for age and body mass index (BMI), were selected as the control group. The mean age of the participants was 34.80 ± 5.37 years old. Standardized procedures were used to measure anthropometric indicators and assess the body composition of each participant. To determine the dietary patterns, a validated and reliable 147-item food frequency questionnaire (FFQ) was administered. Based on the responses to the FFQ, the LLDS was calculated using 12 specific components. Multiple and univariate logistic regression analyses were performed to estimate the associations between LLDS and PCOS, considering various factors.

Findings
In the control group, the mean LLDS was 45.61 ± 9.67; while in the case group, the mean LLDS was 25.10 ± 7.49, respectively (P = 0.001). After adjusting for socioeconomic status (SES), age, protein, fat, physical activity and BMI, the probability of developing PCOS is 69% lower in the third tertiles of LLDS than in the first tertiles (OR = 0.31, CI 95% = 0.15–0.62), (P < 0.001).

Originality/value
The study finds that a higher LLDS correlates with reduced PCOS risk, echoing dietary advice to boost fruits, dairy, vegetables, legumes, poultry and grains while limiting pasta, rice, bread, eggs, red meat, sweets, sugar and hydrogenated fats.
Facile one-pot synthesis and characterization of castor oil-based acrylate oligomer for UV curable wood coating
Authors: Potdar Shubham , Jagtap Ramanand 
Published: June 2024

Purpose
For the sake of sustainable development and environmental preservation, it is crucial to develop UV-curable coatings composed of renewable resources. Castor oil, being both bio-based and economical, serves as the focal point of this research paper. The purpose of this research paper is to synthesize, formulate and apply a UV-curable biobased oligomer ECOSAGMA as a wood coating, with a focus on sustainable development and environmental preservation. Castor oil, being both bio-based and economical, serves as the focal point of this research paper.

Design/methodology/approach
ECOSAGMA was prepared by reacting epoxidized castor oil with sebacic acid, followed by reaction with glycidyl methacrylate through ring opening reaction. The chemical structure of ECOSAGMA was confirmed by Fourier-Transform infrared spectroscopy, 13C-NMR and 1H-NMR spectroscopy. The synthesized oligomer was used for UV-curable coating formulations by combining it with varying amounts of TMPTA from 10 to 40 wt.% and studied for their rheological properties. The UV curable formulations were co-photopolymerized into thin coatings and were thoroughly examined based on thermal, chemical and mechanical properties.

Findings
The UV-cured coating containing ECOSAGMA and TMPTA exhibits exceptional mechanical, chemical and thermal properties, underscoring their potential for deployment in real-world application. It is observed that an increase in the concentration of TMPTA is associated with a notable enhancement in the properties of the UV-cured coatings. The UV-cured wood coating, composed of 40 wt.% TMPTA, demonstrates remarkable stain resistance properties.

Originality/value
In conclusion, by embracing eco-friendly and economically conscious principles., it is evident that this synthesized novel castor oil-based oligomer offers a range of valuable properties to the coating such as stain resistance and thermal stability as well as characteristics such as gloss, hardness, adhesion and chemical resistance.
An investigation on immigration inflows, GDP productivity and knowledge production in selected OECD countries: A panel model analysis
Authors: Afzal Munshi Naser Ibne , Kalra Akash 
Published: June 2024

PurposeThe purpose of this study is to investigate the impact of pervasive immigrant inflows on GDP productivity growth in selected OECD countries, including Australia, Canada, Germany, Italy, New Zealand and the USA. The study aims to consider patent filing residence and non-residence as well as R&D expenditure to see if large immigrant destination countries can accept many immigrants to generate knowledge and creativity and stimulate economic development.Design/methodology/approachThe study uses OECD and WDI data sets from 2000 to 2019 and employs a fundamental correlation matrix and static panel model to analyze the data. The study examines the impact of residential and non-residential patent applications and R&D expenditure on GDP productivity growth in the selected OECD countries.FindingsThe study found an adverse effect for residential patent applications, while non-residential patent application and R&D expenditure variables were strongly linked to GDP productivity. This indicates that to reap the benefits of skilled immigration inflows, the selected OECD countries must devote more resources to research and development and build a knowledge-based economy. This will improve economic efficiency and overall growth.Originality/valueThis paper assists policymakers in comprehending how to effectively utilize immigration inflows in developed and emerging economies in order to construct a future knowledge-based economic system.
The effect of output level, exchange rate and interest rate on inflation in BRIC-T countries
Authors: Akbaş Yusuf Ekrem , Dönmez Zafer , Can Esra 
Published: June 2024

PurposeIn this study, it is analyzed the validity of the exchange rate pass-through (ERPT) effect and the effect of interest rate and output level on the inflation rate (IR) in Brazil, Russia, India, China and Turkey (BRIC-T) between the years 1995Q1 and 2022Q4.Design/methodology/approachThe methods such as the panel unit root test developed by Westerlund (2012), the LM bootstrap panel cointegration test developed by Westerlund and Edgerton (2007), the common correlated effects (CCE) estimator developed by Pesaran (2006) and the augmented mean group (AMG) estimator developed by Eberhardt and Bond (2009) that take into account the cross-section dependency are applied for analysis.FindingsAs a result of the findings, it is determined that the ERPT effect is valid in Turkey, Brazil, Russia, India and China and the cost channel is valid only in China. Finally, it is found out that output level positively affects inflation in Turkey, Brazil, Russia, India and China.Practical implicationsAll these results indicate that the economies of Turkey, Russia, Brazil and India have a fragile structure, especially in terms of inflation. Therefore, the central bank of these countries should maintain exchange-rate stability to implement the inflation-targeting strategy successfully. In this context, central bank independence should be increased in these countries in achieving this objective. Also the results indicate that it is still early to consider whether BRIC-T countries and accordingly the Belt and Road Initiative will be an alternative against the domination of the USA and European Union (EU) on international trade system or it will substitute them.Originality/valueIn this study, it is tested that the impact of interest-rate (NIR), exchange-rate (FER) and output level (IPI) on general level of prices. Besides, it is analyzed that whether production level affects the IR. Also, the study investigates the economic issues such as ERPT effect and cost channel. The study analyzes whether China's Belt and Road Initiative is successful or not. In this study, we used the panel data methods that allow for structural breaks and cross-section dependency. For these reasons, this study differs from other studies in the literature both in terms of scope and methods used.
The export performance of textile and apparel industry of Ethiopia: a comparative study with global emerging exporters
Authors: Gebre Wubishet Mengesha , Birbirsa Zerihun Ayenew , Abegaz Mekonnen Bogale 
Published: June 2024

Purpose
This study aims to assess Ethiopia’s export performance and emerging exporters of textile and apparel products.

Design/methodology/approach
Descriptive research designs were used to investigate textiles and apparel export performance. Quantitative secondary data were collected from the International Trade Center database for 19 years (2004–2022). Data analysis was performed using percentage, Revealed Comparative Advantage (RCA) and Independent t-test using Excel and SPSS version 20.

Findings
Findings show that Ethiopia and emerging exporters of textiles and apparel have fluctuating export performance both in absolute value and percentage of growth. The RCA results revealed that Ethiopia, South Africa, Japan, Russia, Australia and Ghana had comparative disadvantages at first, and then Ethiopia’s index showed improvement to weak and medium levels. Meanwhile, countries such as Madagascar and Cambodia have a stronger comparative advantage than Ethiopia and other countries considered in this study. In addition, the findings also show significant differences between Ethiopia and other emerging exporters of textile apparel, except Egypt.

Practical implications
The findings of this study have significant ramifications for scholars, professionals in the textile sector and decision-makers in legislation.

Originality/value
This study established new trends and extended the application of the RCA index across regions.