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1 – 10 of 54Pooja Darda, Om Jee Gupta and Susheel Yadav
Alexa’s integration in rural primary schools has improved the pedagogy and has created an engaging and objective learning environment. This study investigates the integration…
Abstract
Purpose
Alexa’s integration in rural primary schools has improved the pedagogy and has created an engaging and objective learning environment. This study investigates the integration, with a specific focus on exploring its various aspects. The impact of Alexa’s on students' English vocabulary, comprehension and public speaking are examined. This study aims to provide insights the teachers and highlight the potential of artificial intelligence (AI) in rural education.
Design/methodology/approach
This content analysis study explores the use of Alexa in primary education in rural areas of India. The study focuses on the types of the questions asked by the students and examines the pedagogical implications of these interactions. By analyzing the use of Alexa in rural educational settings, this study aims to contribute to our understanding of how voice assistants are utilized as educational tools in underprivileged areas.
Findings
Alexa significantly improved students' English vocabulary, comprehension and public speaking confidence. Alexa increased school enrollment and retention. Virtual voice assistants like Alexa may improve pedagogy and help India’s rural education. This study shows AI improves rural education.
Research limitations/implications
The study only covers rural India. Self-reported data and observations may bias the study. The small sample size may underrepresent rural educational institutions in India.
Originality/value
Alexa is used to study rural India’s primary education. Voice assistants in rural education are understudied. The study examines Alexa’s classroom use, student questions, and policy and teacher education implications. AI’s education transformation potential addresses UNESCO’s teacher shortage. This novel study examines how AI can improve rural education outcomes and access.
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Liyi Zhang, Mingyue Fu, Teng Fei, Ming K. Lim and Ming-Lang Tseng
This study reduces carbon emission in logistics distribution to realize the low-carbon site optimization for a cold chain logistics distribution center problem.
Abstract
Purpose
This study reduces carbon emission in logistics distribution to realize the low-carbon site optimization for a cold chain logistics distribution center problem.
Design/methodology/approach
This study involves cooling, commodity damage and carbon emissions and establishes the site selection model of low-carbon cold chain logistics distribution center aiming at minimizing total cost, and grey wolf optimization algorithm is used to improve the artificial fish swarm algorithm to solve a cold chain logistics distribution center problem.
Findings
The optimization results and stability of the improved algorithm are significantly improved and compared with other intelligent algorithms. The result is confirmed to use the Beijing-Tianjin-Hebei region site selection. This study reduces composite cost of cold chain logistics and reduces damage to environment to provide a new idea for developing cold chain logistics.
Originality/value
This study contributes to propose an optimization model of low-carbon cold chain logistics site by considering various factors affecting cold chain products and converting carbon emissions into costs. Prior studies are lacking to take carbon emissions into account in the logistics process. The main trend of current economic development is low-carbon and the logistics distribution is an energy consumption and high carbon emissions.
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Haihan Li, Per Hilletofth, David Eriksson and Wendy Tate
This study aims to investigate the manufacturing reshoring decision-making content from an Eclectic Paradigm perspective.
Abstract
Purpose
This study aims to investigate the manufacturing reshoring decision-making content from an Eclectic Paradigm perspective.
Design/methodology/approach
Data were collected through a six-step systematic literature review on factors influencing manufacturing reshoring decision-making. The review is based on 100 peer-reviewed journal papers discussing reshoring decision-making contents published from 2009 to 2022.
Findings
In total, 80 decision factors were extracted and then categorized into resource-seeking (8%), market-seeking (11%), efficiency-seeking (41%) and strategic asset-seeking (16%) advantages. Additionally, 24% of these were identified as hybrid, which means that they were classified into multiple categories. Some decision factors were further identified as reshoring influencing factors (i.e. drivers, enablers and barriers).
Research limitations/implications
Scholars need to consider what other theories can be used or developed to identify and evaluate the decision factors (determinants) of manufacturing reshoring as well as how currently adopted theory can be further advanced to create clearer and comprehensive theoretical frameworks.
Practical implications
This research underscores the importance of developing clearer and more comprehensive theoretical frameworks. For practitioners, understanding the multifaceted nature of decision factors could enhance strategic decision-making regarding reshoring initiatives.
Originality/value
To the best of the authors’ knowledge, this is the first study to investigate the value and practicality of the Eclectic Paradigm in categorizing factors in manufacturing reshoring decision-making content and presents in-depth theoretical classifications. In addition, it bridges the gap between decision factors and influencing factors in the decision-making content research realm.
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Anne Friedrich, Anne Lange and Ralf Elbert
This study identifies and characterizes configurations of generic business models for logistics service providers (LSPs) in the context of industrial additive manufacturing (AM)…
Abstract
Purpose
This study identifies and characterizes configurations of generic business models for logistics service providers (LSPs) in the context of industrial additive manufacturing (AM). A literature-based framework of the AM service supply chain (SC) is developed to embed the generic configurations in their SC context.
Design/methodology/approach
Following an exploratory research design, 17 interviews were conducted with LSPs, LSPs' potential partners and customers for industrial AM services.
Findings
Six generic configurations are identified, the LSP as a Manufacturer, Landlord, Logistician, Connector, Agent and Consultant. The authors outline how these configurations differ in the required locations, partners and targeted customer segments.
Practical implications
The current discussion of reshoring and shorter, decentralized AM SCs confronts LSPs with novel challenges. This study offers guidance for managers of LSPs for designing business models for industrial AM and raises awareness for LSPs' resource and SC implications.
Originality/value
This study contributes to the scarce literature on AM business models for LSPs with in-depth empirical insights. Based on the six identified configurations, this study sets the ground for theorizing about the business models, in particular, the value creation, value proposition and mechanisms for value capture of the business models. In addition, this study suggests how the generic configurations fit the features of specific types of LSPs.
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Jiapeng Wu, Dayu Gao, Cheng Xu and Yanqi Sun
This paper aims to investigate the influence of the regional business environment on local firm innovation, considering various dimensions such as administrative, financial and…
Abstract
Purpose
This paper aims to investigate the influence of the regional business environment on local firm innovation, considering various dimensions such as administrative, financial and legal environments.
Design/methodology/approach
Multiple regression analysis is employed to analyze archival data for firms listed on Chinese stock markets.
Findings
We find that the optimizations of the administrative and financial environments positively affect firm innovation, whereas the legal environment does not exert a similar impact. Our analysis also reveals that the business environment’s optimization significantly influences innovation in firms that are small, non-state-owned and operating in high-tech industries. Furthermore, the business environment acts as a moderating variable in the relationship between firm innovation and firm value.
Research limitations/implications
This study contributes to a more comprehensive understanding of institutional-level determinants of firm innovation, highlighting the nuances of the legal environment and the importance of context-specific analysis, especially in emerging markets like China.
Practical implications
Developing countries can significantly enhance firm innovation by improving the business environment, including the optimization of administrative and financial systems, reducing transaction costs and ensuring capital supply. Tailored legal frameworks and alternative institutional strategies may also be explored.
Social implications
This study explicitly emphasizes the governmental role in promoting firm innovation, shedding light on policy formulation and strategic alignment with local administrative policies.
Originality/value
To the best of our knowledge, this paper is the first to explore the relationship between the business environment and firm innovation using World Bank indicators in an emerging market context, providing novel insights into the unique dynamics of legal, financial and administrative sub-environments.
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Leandro dos Santos, Elsebeth Holmen, Ann-Charlott Pedersen, Maria Flavia Mogos, Eirin Lodgaard and Daryl John Powell
Toyota had mature lean capabilities when developing its supplier network. This paper aims to explore how companies can develop a Toyota-style supplier network (TSN) while their…
Abstract
Purpose
Toyota had mature lean capabilities when developing its supplier network. This paper aims to explore how companies can develop a Toyota-style supplier network (TSN) while their lean capabilities are still evolving.
Design/methodology/approach
Theoretically, this paper relies on the literature on lean maturity levels and lean supplier network development. Empirically, the paper portrays a Toyota-style initiative, detailing the buyer’s efforts to develop internal lean capabilities concurrently with developing lean in its supplier network. It compares the Network for supplier innovation (NSI) initiative with TSN development regarding activities, organizations and knowledge-sharing routines.
Findings
Unlike the sequential development in the case of Toyota, NSI improved performance and capabilities in the buyer’s supplier network by implementing lean in the firm and its supplier network concurrently. Third-party involvement was the key to the initiative’s success.
Research limitations/implications
The findings are based on an in-depth single-case study which allows theoretical generalization but not statistical generalization. Furthermore, the case study concerns an initiative with Norwegian firms during a financial recession. Future studies should consider these limitations on how firms with evolving lean capabilities can develop a TSN-style supplier network and the importance of involving third parties operating in the role of lean master.
Practical implications
This study suggests what buying firms should consider when designing a TSN initiative, enrolling suppliers and engaging third parties that can take on the role of lean master.
Originality/value
Previous research has focused on how mature lean firms develop lean suppliers and networks. This paper extends this to firms whose lean capabilities are still evolving.
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This study aims to propose and develop a new digital collaborative supply chain (CSC) model completely based on the emerging Industry 4.0 technologies. The digital model aims to…
Abstract
Purpose
This study aims to propose and develop a new digital collaborative supply chain (CSC) model completely based on the emerging Industry 4.0 technologies. The digital model aims to support the main factors likely to affect CSC. This proposed model combines the most well-known digital tools such as blockchain technology, Internet of Things (IoT) and cloud computing (CC).
Design/methodology/approach
Motivated by its effective solution to enhance trust, traceability, transparency and minimize costs and risks, the combination of the most well-known digital tools such as blockchain technology, IoT and CC to develop a new digital CSC model is addressed in this research. This study first investigates and conducts a deep review analysis that explores how Industry 4.0 technologies can enable collaboration mechanisms. Second, based on an analysis of literature review, the main factors likely to affect CSC have been identified and analysed. Finally, the authors combine digital tools to support the identified factors to enhance transparency, traceability and trust by proposing a new digital CSC model. This proposed model will be used as a referential guide to encourage and motivate SC actors to collaborate in digital CSC.
Findings
This work provides many important contributions to theory and practice. First, role and impacts of the most well-known digital tools such as blockchain technology, IoT and CC for digitizing CSC have separately presented and developed. Second, the authors conceptualized a framework by developing a new digital CSC model. This conceptual digital model can be used as a referential guide for all SC actors in order to motivate them to collaborate in a modern, intelligent, secure and reliable SC. It can also support all factors affecting CSC.
Originality/value
The originality of this study is first investigating separately the roles and impacts of each digital tool on CSC performance. Second, the authors combine the most well-known digital tools such as blockchain technology, IoT and CC in order to develop an efficient, smart, modern and new digital CSC model. In this combination, CC is used as platform as a service enabling to link and connect the blockchain and IoT to support the main factors affecting CSC. Unlike to digital CSC model with only one digital tool, the proposed model is more realistic since depending on the information to be shared with other actors, the most appropriate tool will be automatically detected and used. This solution offers a large choice to SC actors for real time data and information sharing. In addition, the proposed model will largely enhance traceability, transparency and trust in CSC.
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Cevahir Uzkurt, Emre Burak Ekmekcioglu and Semih Ceyhan
Based on the dynamic capability theory, the purpose of this study is to examine the mediating role of the adaptive capability of small- and medium-sized enterprises (SMEs) on the…
Abstract
Purpose
Based on the dynamic capability theory, the purpose of this study is to examine the mediating role of the adaptive capability of small- and medium-sized enterprises (SMEs) on the relationship between business ties and firm performance. This study also investigates the moderating role of technological turbulence in those relationships.
Design/methodology/approach
Data were collected from 1,265 SME managers in Turkey. Partial least squares analysis, a variance-based structural equation modelling, was applied to examine a mediated moderation model.
Findings
The results support the proposed framework illustrating that business ties are positively related to adaptive capability and firm performance. Moreover, adaptive capability mediates the relationship between business ties and firm performance. The results also indicate that the indirect effect of business ties on firm performance through adaptive capability was moderated by technological turbulence.
Practical implications
SMEs in emerging economies need to enhance their business ties and invest in their adaptive capabilities to increase their performances. This relation becomes more strategic under technologically turbulent environments.
Originality/value
By introducing empirical data from the Turkish emerging context, this paper contributes to our understanding of how SMEs’ relational networks contribute to firm performance. From the dynamic capability perspective, it shows how SMEs use their adaptive capabilities to environmental challenges. It also fills an important gap by showing that environmental uncertainties (specifically technological turbulence) moderate the adaptive capability’s mediating impact on the relationship between business ties and firm performance. The results also provide potential future directions for dynamic capabilities research in emerging contexts.
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Ziming Zhou, Fengnian Zhao and David Hung
Higher energy conversion efficiency of internal combustion engine can be achieved with optimal control of unsteady in-cylinder flow fields inside a direct-injection (DI) engine…
Abstract
Purpose
Higher energy conversion efficiency of internal combustion engine can be achieved with optimal control of unsteady in-cylinder flow fields inside a direct-injection (DI) engine. However, it remains a daunting task to predict the nonlinear and transient in-cylinder flow motion because they are highly complex which change both in space and time. Recently, machine learning methods have demonstrated great promises to infer relatively simple temporal flow field development. This paper aims to feature a physics-guided machine learning approach to realize high accuracy and generalization prediction for complex swirl-induced flow field motions.
Design/methodology/approach
To achieve high-fidelity time-series prediction of unsteady engine flow fields, this work features an automated machine learning framework with the following objectives: (1) The spatiotemporal physical constraint of the flow field structure is transferred to machine learning structure. (2) The ML inputs and targets are efficiently designed that ensure high model convergence with limited sets of experiments. (3) The prediction results are optimized by ensemble learning mechanism within the automated machine learning framework.
Findings
The proposed data-driven framework is proven effective in different time periods and different extent of unsteadiness of the flow dynamics, and the predicted flow fields are highly similar to the target field under various complex flow patterns. Among the described framework designs, the utilization of spatial flow field structure is the featured improvement to the time-series flow field prediction process.
Originality/value
The proposed flow field prediction framework could be generalized to different crank angle periods, cycles and swirl ratio conditions, which could greatly promote real-time flow control and reduce experiments on in-cylinder flow field measurement and diagnostics.
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Tze Yin Khaw, Azlan Amran and Ai Ping Teoh
This paper aims to explore the factors affecting cybersecurity implementation in organizations in various countries and develop a cybersecurity framework to improve cybersecurity…
Abstract
Purpose
This paper aims to explore the factors affecting cybersecurity implementation in organizations in various countries and develop a cybersecurity framework to improve cybersecurity practices within organizations for cybersecurity risk management through a systematic literature review (SLR) approach.
Design/methodology/approach
This SLR adhered to RepOrting Standards for Systematics Evidence Syntheses (ROSES) publication standards and used various research approaches. The study’s article selection process involved using Scopus, one of the most important scientific databases, to review articles published between 2014 and 2023.
Findings
This review identified the four main themes: individual factors, organizational factors, technological factors and governmental role. In addition, nine subthemes that relate to these primary topics were established.
Originality/value
This research sheds light on the multifaceted nature of cybersecurity by exploring factors influencing implementation and developing an improvement framework, offering valuable insights for researchers to advance theoretical developments, assisting industry practitioners in tailoring cybersecurity strategies to their needs and providing policymakers with a basis for creating more effective cybersecurity regulations and standards.
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