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1 – 10 of 645Tan Zhang, Zhanying Huang, Ming Lu, Jiawei Gu and Yanxue Wang
Rotating machinery is a crucial component of large equipment, and detecting faults in it accurately is critical for reliable operation. Although fault diagnosis methods based on…
Abstract
Purpose
Rotating machinery is a crucial component of large equipment, and detecting faults in it accurately is critical for reliable operation. Although fault diagnosis methods based on deep learning have been significantly developed, the existing methods model spatial and temporal features separately and then weigh them, resulting in the decoupling of spatiotemporal features.
Design/methodology/approach
The authors propose a spatiotemporal long short-term memory (ST-LSTM) method for fault diagnosis of rotating machinery. The authors collected vibration signals from real rolling bearing and gearing test rigs for verification.
Findings
Through these two experiments, the authors demonstrate that machine learning methods still have advantages on small-scale data sets, but our proposed method exhibits a significant advantage due to the simultaneous modeling of the time domain and space domain. These results indicate the potential of the interactive spatiotemporal modeling method for fault diagnosis of rotating machinery.
Originality/value
The authors propose a ST-LSTM method for fault diagnosis of rotating machinery. The authors collected vibration signals from real rolling bearing and gearing test rigs for verification.
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Xi Yu, Awudu Abdulai and Dongmei Li
This study aims to examine farmers' decision to use smartphone agricultural applications (SAAs) and how SAAs adoption impact their land transfer behaviors in terms of the current…
Abstract
Purpose
This study aims to examine farmers' decision to use smartphone agricultural applications (SAAs) and how SAAs adoption impact their land transfer behaviors in terms of the current land transfer-in area (LTA) and the future willingness to renew land transfer-in after it expires (WTR).
Design/methodology/approach
This study provides empirical evidence on the relationship between farmers' use of SAAs and land transfer choice, using a field survey data of 752 rural farm households in 2020 from Sichuan province of China. The endogenous switching models are employed to address potential self-selection bias associated with voluntary SAAs use and to quantitatively examine the impacts of SAAs use on land transfer choice.
Findings
The empirical results reveal that SAAs significantly improves the probability of transfer-in of more land by 39.10%. We find SAAs use has heterogeneous impacts on land transfer-in choice in the groups of agricultural technology, extension service, marketing and credit. Besides, we also find that SAAs use exerts highly positive and significant impact on farmers with less land area transfer-in. Moreover, SAAs can increase the probability of farmers' willingness to renew the land transfer-in by 30%.
Originality/value
To the best of our knowledge, this study is the first to explore the quantitative relationship between the use of SAAs and farm households' land transfer choice. The findings of this work can provide policy-related insights to help government promote the development of digital applications in the agricultural sector.
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Nida Rahman and Krishan Sharma
Regional comprehensive economic partnership (RCEP) is understood as the world's largest trading bloc given its contribution to the world output (30%). The mega trade bloc brings…
Abstract
Purpose
Regional comprehensive economic partnership (RCEP) is understood as the world's largest trading bloc given its contribution to the world output (30%). The mega trade bloc brings together 15 countries of East Asia, Southeast Asia and Oceania to eliminate tariff and non-tariff barriers in goods and services trade. The study suggests the importance of sector specific reforms for Malaysia to strengthen domestic capability.
Design/methodology/approach
The analytical framework constructs upon the partial equilibrium analysis and uses WITS SMART simulations.
Findings
The study finds that Malaysia's elimination of tariffs under the RCEP will cause a surge in imports from developed member countries of RCEP like Australia, South Korea and Japan. The study also finds a trade diversion in countries such as India. The empirical results establishes that RCEP would further strengthen intra-ASEAN trade.
Research limitations/implications
The study explores select sectors of the manufacturing industry in Malaysia.
Practical implications
The implementation of RCEP would impact the manufacturing sector immensely, especially in sectors like electrical machinery and equipment and inorganic chemicals, which are two of the major trading commodities of the Malaysian economy.
Social implications
Any trade agreement has a larger impact on the society. It may raise income, boost the consumer preferences and create or erode consumer welfare. The study reports the consumer welfare effect of the implementation of RCEP in Malaysia.
Originality/value
The study is the first attempt to do a partial equilibrium analysis for the electrical machinery and equipment sector and inorganic chemicals sector of Malaysia using both aggregated and disaggregated data at HS two-digit and HS six-digit level.
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Smart manufacturing is revolutionizing the manufacturing industry by shifting the focus from traditional manufacturing to a more intelligent, interconnected and responsive system…
Abstract
Purpose
Smart manufacturing is revolutionizing the manufacturing industry by shifting the focus from traditional manufacturing to a more intelligent, interconnected and responsive system. Despite being the backbone of the economy and despite the government’s efforts in supporting and encouraging the transformation to smart manufacturing, small and medium enterprises (SMEs) have been struggling to transform their operations. This study aims to identify the challenges for SMEs’ transformation and the benefits they can get from this transformation, following a systematic review of existing literature.
Design/methodology/approach
A systematic review of existing literature has been performed to identify the peer-reviewed journal articles that focus on smart manufacturing for SMEs. First, a comprehensive list of keywords relevant to the review questions are identified. Second, Scopus and Web of Science databases were then used to search for articles, applying filters for English language and peer-reviewed status. Third, after manually assessing abstracts for relevance, 175 articles are considered for further review and analysis.
Findings
The benefits and challenges of SMEs’ transformation to smart manufacturing are identified. The identified challenges are categorized using the Smart Industry Readiness Index (SIRI) framework. Further, to address the identified challenges and initiate the SME’s transition toward smart manufacturing, a framework has been proposed that shows how SMEs can start their transition with minimum investment and existing resources.
Originality/value
Several studies have concentrated on understanding how smart manufacturing enhances sustainability, productivity and preventive maintenance. However, there is a lack of studies comprehensively analyzing the challenges for smart manufacturing adoption for SMEs. The originality of this study lies in identifying the challenges and benefits of smart manufacturing transformation and proposing a framework as a roadmap for SMEs' smart manufacturing adoption.
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This study aims to investigate the influence and impact mechanism of capital tax incentives on firm innovation.
Abstract
Purpose
This study aims to investigate the influence and impact mechanism of capital tax incentives on firm innovation.
Design/methodology/approach
This study employs the difference-in-differences (DID) method, in conjunction with the exogenous impact of accelerated depreciation (AD) pilot policy. This study selects Chinese listed companies from 2010 to 2017 as the research sample.
Findings
Firstly, AD exerts a substantial positive effect on the quantity and quality of the innovation output of firms, and the positive impact results primarily from heightened investment in fixed assets, particularly, machinery and equipment. Secondly, the influence of the policy is pronounced in non-state-owned enterprises, mature enterprises, less capital-intensive enterprises and non-high-tech industries, which all exhibit strong innovation incentives. Lastly, the tax incentive policy significantly stimulates firm innovation in the short term, but its long-term impact on innovation incentives lacks statistical significance.
Originality/value
This study highlights the significance of capital tax incentives in facilitating the innovation process in firms.
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Wenhua Liu, Zekai He and Qi Wang
This paper explores the relationship between state-led urbanization and primary industry development using the difference-in-differences (DiD) method.
Abstract
Purpose
This paper explores the relationship between state-led urbanization and primary industry development using the difference-in-differences (DiD) method.
Design/methodology/approach
The study uses the DiD method.
Findings
Exploiting county-city mergers during 2010–2018, the key strategy to expand the city outward and promote urbanization on the urban fringe by local government, the authors find that county-city mergers led to the growth of primary industry decline by 4.23%. The result can be explained by the loss of essential production factors, including land and labor used for farming. In addition, the negative effect is more pronounced for counties with more substantial manufacturing. The results indicate that urbanization in China relocates land and labor; however, it does not improve the efficiency of agricultural output.
Originality/value
This paper contributes to the understanding of urbanization and rural development from the perspective of the primary industry by showing production factor redistribution. Second, this study complements the literature on local government mergers.
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Chanapa Jindain and Bhumiphat Gilitwala
The purpose of this study was to investigate the factors impacting the intermediating variable of employee engagement toward employee performance in a hybrid working organization…
Abstract
Purpose
The purpose of this study was to investigate the factors impacting the intermediating variable of employee engagement toward employee performance in a hybrid working organization in Bangkok, Thailand.
Design/methodology/approach
This study uses secondary data analysis and an archival study; the primary data were gathered from 370 employees who are working in a hybrid model environment in a private agricultural machinery company. To construct a new conceptual framework, this study adopted four frameworks from the previous research.
Findings
Perceived organizational support and trust and respect in the organization are found to have a significant positive impact on employee engagement. Moreover, there is a significant positive impact of the employee engagement on employee performance in a hybrid working model.
Research limitations/implications
For hybrid work environments, the research focused mainly on the emotional themes of perceived support, trust and respect in the organization. Therefore, there would be many factors that could possibly affect those dependence variables in any environment, which will have to be investigated more in future research. Either in the organization or in the company, many departments and business units operates for the company, but the researcher specifies only the business units or departments that now use the hybrid working model.
Practical implications
This study focuses on a case study of an agricultural machinery company, which likely produces different results than other industries, other industries may produce different results.
Social implications
Hybrid working models can blur the boundaries between work and personal life, potentially leading to increased stress and burnout. Organizations should prioritize work-life balance and employee well-being by promoting flexible schedules, encouraging breaks and time off, and providing resources for mental health support.
Originality/value
The organization which is operating among a hybrid working model, the increasing of perceived organizational support and trust and respect level, has positively increase the employee engagement toward enhancing the employee performance.
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Rolling element bearings (REBs) are commonly used in rotating machinery such as pumps, motors, fans and other machineries. The REBs deteriorate over life cycle time. To know the…
Abstract
Purpose
Rolling element bearings (REBs) are commonly used in rotating machinery such as pumps, motors, fans and other machineries. The REBs deteriorate over life cycle time. To know the amount of deteriorate at any time, this paper aims to present a prognostics approach based on integrating optimize health indicator (OHI) and machine learning algorithm.
Design/methodology/approach
Proposed optimum prediction model would be used to evaluate the remaining useful life (RUL) of REBs. Initially, signal raw data are preprocessing through mother wavelet transform; after that, the primary fault features are extracted. Further, these features process to elevate the clarity of features using the random forest algorithm. Based on variable importance of features, the best representation of fault features is selected. Optimize the selected feature by adjusting weight vector using optimization techniques such as genetic algorithm (GA), sequential quadratic optimization (SQO) and multiobjective optimization (MOO). New OHIs are determined and apply to train the network. Finally, optimum predictive models are developed by integrating OHI and artificial neural network (ANN), K-mean clustering (KMC) (i.e. OHI–GA–ANN, OHI–SQO–ANN, OHI–MOO–ANN, OHI–GA–KMC, OHI–SQO–KMC and OHI–MOO–KMC).
Findings
Optimum prediction models performance are recorded and compared with the actual value. Finally, based on error term values best optimum prediction model is proposed for evaluation of RUL of REBs.
Originality/value
Proposed OHI–GA–KMC model is compared in terms of error values with previously published work. RUL predicted by OHI–GA–KMC model is smaller, giving the advantage of this method.
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The purpose of this study is to define and develop a new technological development path for latecomer firms in developing countries.
Abstract
Purpose
The purpose of this study is to define and develop a new technological development path for latecomer firms in developing countries.
Design/methodology/approach
An analytical framework for development based on the technological capability (TC) dimensions is developed and examined in the drilling sector. Since the process of TC accumulation is dynamic, the case study approach is the best method for an exploratory theory-building study. Through a comparative case study of two Iranian drilling contractors, a new path for the technological development of latecomer oil service companies is proposed.
Findings
The study of two cases indicates that despite having similar scope and levels of TC, one of them demonstrated superior technical performance. To address this difference, the concept of operational efficiency is introduced which is considered the outcome of increasing the depth of TC.
Practical implications
Although upgrading the level of technological and innovation capability is an important path for technological development, latecomers that suffer from various disadvantages can perform their routine activities with superior performance and develop through their basic operational/production capabilities. Also, specialized indicators designed for assessing the level and depth of TC in the drilling industry have important insights for evaluating the technological and competitive position of oil service companies.
Originality/value
To the best of the author’s knowledge, this study takes the first step in defining and elaborating on the concept of depth of TC as a development path for latecomers. It also introduced a novel approach to the global operational/production efficiency frontier as a target for their catch-up.
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Rajali Maharjan and Hironori Kato
This study investigates whether logistics and supply chain resilience strategies (SCREST) can help mitigate the negative impacts of disruptions on firm performance and logistics…
Abstract
Purpose
This study investigates whether logistics and supply chain resilience strategies (SCREST) can help mitigate the negative impacts of disruptions on firm performance and logistics and supply chain (SC) activities of companies, using the COVID-19 pandemic as a case study.
Design/methodology/approach
The authors collected primary data on the implementation of different types of SCRESTs and measured the impact of COVID-19 in terms of firm performance and logistics and SC metrics through a survey of Japanese manufacturing companies in four sectors. The authors used these data to illustrate whether the companies benefitted from SCRESTs in mitigating the negative impacts of COVID-19. A questionnaire comprising structured and open-ended questions was sent to 8,000 companies all over Japan that met the selection criteria, using a combination of mail and web-based media. The respondents were logistics and SC professionals. A combination of qualitative and quantitative analysis was performed for data analysis and interpretation.
Findings
Research conducted within the case of the Japanese context revealed that findings varied depending on the methodology applied. The use of a direct analysis approach and qualitative analysis suggested that the implementation of SCRESTs is beneficial in addressing the negative impacts of COVID-19 on firm performance and logistics and SC activities, whereas the application of indirect analysis approach yielded mixed results. The analysis also indicated a shift in the preferred SCRESTs during COVID-19.
Originality/value
To the best of the authors’ knowledge, this is the first study to examine the benefits of implementing SCRESTs using primary data from the manufacturing sector of Japan. Furthermore, empirical research on this topic is generally lacking.
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