Michael Wang, Samsul Islam and Wei Yang
Supply chain risk (SCR) has been extensively explored in various sectors, yet there is a notable scarcity of SCR studies in the dairy industry. This study aims to identify the…
Abstract
Purpose
Supply chain risk (SCR) has been extensively explored in various sectors, yet there is a notable scarcity of SCR studies in the dairy industry. This study aims to identify the primary and distinctive risks in the dairy supply chain (DSC), propose a typological model for SCR, highlight challenges specific to the DSC and offer mitigation strategies.
Design/methodology/approach
We employ a systematic literature review to collect and review relevant research articles published between 2010 and 2019 to identify the main risks and mitigation strategies associated with the DSC, enabling the construction of a typological model of DSC risks.
Findings
Results of the systematic review of the SCR literature show that the main DSC risks include on-farm risk (e.g. risks originating from the farming system), off-farm risk (e.g. supply risk, demand risk and manufacturing risk) and inherent SCR (e.g. logistics risk, information risk and financial risk). Notably, we find that the farming system plays a key role in today’s agricultural supply chain operations, indicating the importance of considering on-farm risk in the entire DSC. Additionally, mitigation strategies are located in response to the identified DSC risks by the typology of DSC risks.
Originality/value
This paper is the first attempt to develop a typological model of SCR for the dairy industry by a systematic literature review. The findings contribute to providing a comprehensive understanding of DSC risks by bridging the gap of ignoring the on-farm risks of the DSC in the existing literature. The typology may serve as a guide in practice to develop mitigation strategies in response to DSC risks.
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Nguyen Thanh Viet, Denver Banlasan and Do Tien Sy
Adequate, reliable, and efficient urban infrastructure systems (UIS) are fundamental to sustainable development, social mobility, and economic vitality. As communities…
Abstract
Adequate, reliable, and efficient urban infrastructure systems (UIS) are fundamental to sustainable development, social mobility, and economic vitality. As communities continuously rely on basic infrastructure services to support their daily communal functions, major components of UIS are subject to heavy use, and thus rapidly deteriorate over time; hence, it is critical that efficient infrastructure management strategies practices are in place. As current strategies remain confronted with various limitations including adaptability to changing conditions, lack of public engagement, and cost-effectiveness, this study explores social media data mining as an approach to revitalise and support current urban infrastructure monitoring strategies by extracting valuable insights from public opinion. Twitter messages or ‘Tweets’ pertaining to public infrastructure in The Philippines were collected and analysed to identify recurring issues in public infrastructure, emerging topics in public discussions, and the overall perception of the public on infrastructure services. This study presents a topic model that extracts dominant topics from aggregated social media data and a sentiment analysis model that determines public opinion sentiment in relation to different urban infrastructure components. The findings of this study highlight the potential of social media data mining to surpass the limits of conventional data collection techniques and the importance of public opinion as a key driver for a more user-involved decision-making in infrastructure management and as an important social aspect that can be utilised to support planning and response strategies in routine maintenance, preservation, and improvement of UIS.
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Haiyi Zong, Guangbin Wang and Dongping Cao
As the foundation of social and economic development, infrastructure development projects are characterized by large initial investment, high technical requirements and thus…
Abstract
Purpose
As the foundation of social and economic development, infrastructure development projects are characterized by large initial investment, high technical requirements and thus generally delivered through complex contractor–subcontractor collaboration chains. This study aims to characterize the complexity of collaborative networks between contractors and subcontractors for infrastructure development through comparing the structural characteristics and the formation mechanisms of contractor–subcontractor collaborative networks for the following two different types of infrastructure: public works (PWCN) owned and operated by government agencies, and public utilities (PUCN) owned and operated by nongovernment agencies.
Design/methodology/approach
Based on the method of stochastic actor-oriented models and the longitudinal dataset of National Quality Award Projects in China during 2001–2020, this study compares how the structural characteristics of project-based collaborative networks between contractors and subcontractors for the two types of projects are different and how related micro-mechanisms, including both structure-based endogenous network effects and attribute-based exogenous homophily effects (institutional, organizational and geographical homophily), collectively underpin the formation of the networks.
Findings
The empirical results provide evidence that while the two networks are both characterized by relatively low levels of network density, PWCN is more globally connected around a minority of superconnected contractors as compared with PUCN. The results further reveal that compared with PUCN, the formation of PWCN is more significantly related to the structure-based anti in-isolates effect, suggesting that PWCN is more open for new entrant subcontractors. With regard to the attribute-based homophily effects, the results provide evidence that while both significantly and positively related to the effects of organizational (same company group) and geographical homophily (same location), the formation of PWCN and PUCN is oppositely driven by the institutional homophily effect (same ownership type).
Originality/value
As an exploratory effort of using network perspective to investigate the formation mechanisms of contractor–subcontractor relationships in the infrastructure development domain, this study contributes to a network and self-organizing system view of how contractors select subcontractors in different types of infrastructure projects. The study also provides insights into how contractor–subcontractor collaborative relationships can be better manipulated to promote the development of complex infrastructure in different contexts.
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Soohyung Joo, Jennifer Hootman and Marie Katsurai
This study aims to explore knowledge structure and research trends in the domain of digital humanities (DH) in the recent decade. The study identified prevailing topics and then…
Abstract
Purpose
This study aims to explore knowledge structure and research trends in the domain of digital humanities (DH) in the recent decade. The study identified prevailing topics and then, analyzed trends of such topics over time in the DH field.
Design/methodology/approach
Research bibliographic data in the area of DH were collected from scholarly databases. Multiple text mining techniques were used to identify prevailing research topics and trends, such as keyword co-occurrences, bigram analysis, structural topic models and bi-term topic models.
Findings
Term-level analysis revealed that cultural heritage, geographic information, semantic web, linked data and digital media were among the most popular topics in the recent decade. Structural topic models identified that linked open data, text mining, semantic web and ontology, text digitization and social network analysis received increased attention in the DH field.
Originality/value
This study applied existent text mining techniques to understand the research domain in DH. The study collected a large set of bibliographic text, representing the area of DH from multiple academic databases and explored research trends based on structural topic models.
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Eliza Nor, Tajul Ariffin Masron and Xiang Hu
This study analyzes the impact of exchange rate volatility (ERV) on inbound tourist arrivals from four ASEAN countries namely Indonesia, the Philippines, Singapore, and Thailand…
Abstract
This study analyzes the impact of exchange rate volatility (ERV) on inbound tourist arrivals from four ASEAN countries namely Indonesia, the Philippines, Singapore, and Thailand during 1970–2017. Volatility in the exchange rates between the tourist currency and ringgit Malaysia is measured using the Generalized Autoregressive Conditional Heteroskedasticity model. The results from Autoregressive Distributed Lagged models indicate that ERV has no significant impact on tourist arrivals from ASEAN to Malaysia. This implies that tourists from these countries may not be sensitive to ERV when choosing Malaysia as their travel destination. There are two possible explanations for the results. First, Malaysian ringgit has been depreciating against major currencies and regional currencies in recent years, which makes ringgit relatively cheaper than other ASEAN currencies. Second, the empirical results of the study support the argument that ERV has a more serious impact on tourist spending compared to tourist arrivals.
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The main purpose of this editorial is to combine the philosophies of learning from the Eastern and the Western cultures, offer some inspiration to researchers, and promote unique…
Abstract
Purpose
The main purpose of this editorial is to combine the philosophies of learning from the Eastern and the Western cultures, offer some inspiration to researchers, and promote unique and interesting contributions to the literature in Chinese human research management (HRM) research.
Design/methodology/approach
To illustrate the Eastern ways of thinking, the author selects two interesting Chinese words, uses reverse‐engineering, and demonstrates how our ancestors used rich, deep, and powerful meanings to design these Chinese words (Graphic 1) and also explores the meaning of knowledge or wisdom. They also reflect the Western culture and recent management literature.
Findings
The paper shows how researchers need to follow philosophical thoughts of the East and the West; study and evaluate the rich literature carefully; think deeply in order to challenge general assumptions and ask novel, original, and meaningful research questions; provide practical new knowledge; and make a significant contribution to the literature.
Originality/value
The paper promotes unique and interesting contributions to the literature in Chinese HRM research.
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This study aims to propose an integrated model based on the DeLone and McLean Information System Success Model (DMISS) to examine whether quality factors (system, service and…
Abstract
Purpose
This study aims to propose an integrated model based on the DeLone and McLean Information System Success Model (DMISS) to examine whether quality factors (system, service and information) can affect user satisfaction and performance of cloud-based marketing systems.
Design/methodology/approach
Recently, technologies change quickly, innovation becomes a vital base of productivity and sustainable growth of businesses is widely accepted. Cyber-physical system technologies help industries change production and marketing cycles according to customers’ needs in real-time. In addition, processing information through cloud service helps companies meet customer needs. The advantages of cloud technology also make it easier for companies to quickly collect the latest data from various sources, making it more effective in decision-making. This research recommends cloud-based marketing to help companies maximize their revenue by providing useful information and better quality for business development. The data were gathered from China automotive companies’ customers. A total of 220 questionnaires were distributed, and 165 (82.5%) usable questionnaires were analyzed using structural equation modeling.
Findings
This study verified that costumers’ perceived information quality, system quality and service quality positively caused the user satisfaction in the cloud-based marketing system.
Practical implications
This paper presents beneficial advice for improving cloud-based marketing systems. Besides, the topic is relevant to cloud-based marketing systems’ success. A better understanding of the impact of intention to use and user satisfaction on cloud-based marketing systems could significantly enhance companies’ success. This paper’s theoretical and practical contributions are expressed to guide organizations and policymakers in increasing cloud-based marketing systems acceptance.
Originality/value
This study empirically tests the relationship of quality factors and performance outcome of cloud-based marketing system through a model based on DeLone and McLean theory. This study bridges the research gap by identifying the factors that drive the adoption of cloud-based services in marketing and the impact of user satisfaction and intention to use on the cloud-based marketing system performance in the case of china companies.
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Yan Guo, Qichao Tang, Haoran Wang, Mengjing Jia and Wei Wang
The rise of artificial intelligence (AI) and machine learning has largely promoted the emergence of “autonomous decision-making” (ADM). This paper aims to establish a personalized…
Abstract
Purpose
The rise of artificial intelligence (AI) and machine learning has largely promoted the emergence of “autonomous decision-making” (ADM). This paper aims to establish a personalized artificial intelligent housekeeper (AIH) that knows more about our hobbies, habits, personality traits, and shopping needs than ourselves and can replace us to do some habitual purchasing behavior.
Design/methodology/approach
We propose an AI decision-making method based on machine learning algorithm, a novel framework for personalized customer preference and purchase. First, the method uses interactive big data to predict a potential consumer’s decision possibility. Then, the method mines the correlation between consumer decision possibility and various factors affecting consumer behavior. Finally, the machine learning algorithm is used to estimate the consumer’s purchase decision according to the comprehensive influencing factors data of the target consumer.
Findings
The experimental results show that the method can predict the regular consumption behavior of consumers in advance and make accurate decision-making behavior. It can find correlations from a large amount of data to help predict many simple purchase decisions in our life, and become our AIH.
Originality/value
This study introduces a new approach that not only has the auxiliary decision-making function but also has the decision-making function. These findings contribute to the research on automated decision-making process of AI and on human–technology interaction by investigating how data attributes consumer purchase decision to AI.
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Lixiang Li, Hongxia Ge and Rongjun Cheng
This paper aims to put forward an extended lattice hydrodynamic model, explore its effects on alleviating traffic congestion and provide theoretical basis for traffic management…
Abstract
Purpose
This paper aims to put forward an extended lattice hydrodynamic model, explore its effects on alleviating traffic congestion and provide theoretical basis for traffic management departments and traffic engineering implementation departments.
Design/methodology/approach
The control method is applied to study the stability of the new model. Through nonlinear analysis, the mKdV equation representing kink-antikink soliton is acquired.
Findings
The predictive effect and the control signal can enhance the traffic flow stability and reduce the energy consumption.
Originality/value
The predictive effect and feedback control are first considered in lattice hydrodynamic model simultaneously. Numerical simulations demonstrate that these two factors can enhance the traffic flow stability.
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Muhammed Akin and Muhammed Ali Yetgin
Introduction: The difficulties and restrictions faced during the pandemic have led various organizations to offer online services. Organizations with the necessary infrastructure…
Abstract
Introduction: The difficulties and restrictions faced during the pandemic have led various organizations to offer online services. Organizations with the necessary infrastructure have adapted more seamlessly to this shift, while unprepared organizations have faced significant challenges. Recognizing the increasing importance of digital transformation, the banking sector, as a critical player in this process, has been widely examined in the literature.
Purpose: The digitization of banking has enabled faster and more convenient access to banking services. It is crucial to investigate how customer experience, shaped by the services provided by customer-centric banking institutions, impacts customer loyalty and satisfaction. This study focuses on data collected in Ankara, the capital city of Turkiye.
Methodology: Data were collected from 564 participants through a face-to-face, online survey. Fifty-four participants were excluded from the study due to non-use of digital banking or being under 18.
Findings: We found that money transfer was the most frequent digital banking transaction. As a result of the research, we understood that there is a statistically significant relationship between customer experience and customer loyalty and satisfaction, and there was no statistically significant relationship between gender and these values.