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1 – 10 of 649Yiping Jiang, Shanshan Zhou, Jie Chu, Xiaoling Fu and Junyi Lin
This paper aims to explore blockchain integration strategies within a three-level livestock meat supply chain in which consumers have a preference for quality trust in livestock…
Abstract
Purpose
This paper aims to explore blockchain integration strategies within a three-level livestock meat supply chain in which consumers have a preference for quality trust in livestock meat products. The paper investigates three questions: First, how does consumers’ preference for quality trust affect blockchain integration and transaction decisions among supply chain participants? Second, under what circumstances will retailers choose to participate in the blockchain? Finally, how can other factors such as blockchain costs and supplier–retailer partnership value affect integration decisions?
Design/methodology/approach
This paper formulates a supply chain network equilibrium model and employs the logarithmic-quadratic proximal prediction-correction method to obtain equilibrium decisions. Extensive numerical studies are conducted using a pork supply chain network to analyze the implications of blockchain integration for different supply chain participants.
Findings
The results reveal several key insights: First, suppliers’ increased blockchain integration, driven by higher quality trust preference, can negatively affect their profits, particularly, with excessive trust preferences and high blockchain costs. Second, an increase in consumers’ preference for quality trust expands the range of unit operating costs for retailers engaging in blockchain. Finally, the supplier–retailer partnership drives retailer blockchain participation, facilitating enhanced information sharing to benefit the entire supply chain.
Originality/value
This study provides original insights into blockchain integration strategies in an agricultural supply chain through the application of the supply chain network equilibrium model. The investigation of several key factors on equilibrium decisions provides important managerial implications for different supply chain participants to address consumers’ preference for quality trust and enhance overall supply chain performance.
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Brian Briggeman, Luke Byers, Jennifer Ifft, Ryan Kuhns, Noah Miller and Jisang Yu
The growth of lending from nontraditional lenders may pose challenges for official US Department of Agriculture (USDA) farm sector debt estimates, but it is difficult to find data…
Abstract
Purpose
The growth of lending from nontraditional lenders may pose challenges for official US Department of Agriculture (USDA) farm sector debt estimates, but it is difficult to find data to assess official estimates. The purpose of this study is to examine whether debt provided by nontraditional lenders is accurately accounted for in official estimates.
Design/methodology/approach
We compare traditional and nontraditional lending data from farm equipment lien collateral values and the USDA Agricultural Resource Management Survey (ARMS). After analyzing trends in equipment lending implied by farm equipment lien data and ARMS, we estimate whether changes in farm equipment lien values predict changes in equipment debt reported in ARMS and whether lender type influences that relationship.
Findings
We find that credit provided by nontraditional lenders is likely underreported in ARMS. Our econometric model shows that equipment debt volumes for nontraditional lenders are consistently lower than traditional loan volumes in ARMS across a variety of model specifications. We also find that an increase in lien values for nontraditional lenders is less likely to predict an increase in ARMS equipment debt volumes than an increase for traditional lenders.
Practical implications
Official farm sector debt estimates may not fully account for nontraditional lenders.
Originality/value
This study demonstrates how the growth of nontraditional lending poses challenges for estimating US farm sector debt. We evaluate farm sector debt estimates and advance knowledge of the role of nontraditional lenders in farm equipment credit provision. The farm equipment lien dataset provides a rich source of novel data for research on local and national equipment debt and investment.
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Yinghong Li, Wei Tan, Wenjie Pei and Guorui Zhu
The purpose of this paper is to investigate the effect of NaCl solution with different concentrations on impact-sliding fretting corrosion behavior of Inconel 690TT steam…
Abstract
Purpose
The purpose of this paper is to investigate the effect of NaCl solution with different concentrations on impact-sliding fretting corrosion behavior of Inconel 690TT steam generator heat transfer tubes.
Design/methodology/approach
The optical 3D profiler was used to measure the wear profile and calculated the wear volume. Corrosion behavior was studied using open circuit potential monitoring and potentiodynamic polarization testing. The morphologies and elemental distributions of wear scars were analyzed using scanning electron microscopy and energy-dispersive spectroscopy. The synergism of wear and corrosion was analyzed according to the ASTM G119 standard.
Findings
The corrosion tendency reflected by OCP and the corrosion current calculated by Tafel both increased with the increase of NaCl concentration. The total volume loss of the material increased with concentration, and it was known from the synergism that the volume loss caused by corrosion-enhanced wear accounted for the largest proportion, while the wear-enhanced corrosion also made a greater contribution to volume loss than tangential fretting corrosion. Through the analysis of the material morphologies and synergism of wear and corrosion, the damage mechanism was elucidated.
Originality/value
The research findings can provide reference for impact-sliding fretting corrosion behavior of Inconel 690TT heat transfer tubes in NaCl solution with different concentrations.
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Rudrajeet Pal and Erik Sandberg
The purpose of this study is to explore the antecedents of uncaptured sustainable value and strategies to generate opportunities to capture it in the circular supply chain of…
Abstract
Purpose
The purpose of this study is to explore the antecedents of uncaptured sustainable value and strategies to generate opportunities to capture it in the circular supply chain of post-consumer used clothing.
Design/methodology/approach
This study is based on an inductive analysis of 21 semi-structured interviews conducted with various stakeholders in the circular clothing supply chain (for-profit and not-for-profit) using the value mapping approach, as previously applied in the literature on sustainable business models.
Findings
Fifteen antecedents of uncaptured sustainable value, and thirteen value opportunity strategies were revealed that hinder or generate multi-dimensional value types. Economic value is impacted the most, while there is lack of explicit understanding of the impact of these antecedents and strategies on environmental and social value capture. From a multi-stakeholder perspective, the ecosystem is emerging as new for-profit actors are developing novel process technologies, while not-for-profit actors are consolidating their positions by offering new service options. There is also an emerging “coopetition” between the different stakeholders.
Research limitations/implications
More granularity in the different types of uncaptured value could be considered, and external supply chain stakeholders, such as the government, could be included, leading to more detailed value mapping.
Practical implications
This research provides practitioners with a value-mapping tool in circular clothing supply chains, thus providing a structured approach to explore, analyse and understand uncaptured value and value opportunities.
Originality/value
This extended value perspective draws upon the value-mapping approach from the sustainable business model literature and applies it in the context of the circular clothing supply chain. In doing so, this research illustrates circular clothing supply chains in a new way that facilitates an improved understanding of multi-dimensional and multi-stakeholder value for embedded actors.
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Patrik Jonsson, Johan Öhlin, Hafez Shurrab, Johan Bystedt, Azam Sheikh Muhammad and Vilhelm Verendel
This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?
Abstract
Purpose
This study aims to explore and empirically test variables influencing material delivery schedule inaccuracies?
Design/methodology/approach
A mixed-method case approach is applied. Explanatory variables are identified from the literature and explored in a qualitative analysis at an automotive original equipment manufacturer. Using logistic regression and random forest classification models, quantitative data (historical schedule transactions and internal data) enables the testing of the predictive difference of variables under various planning horizons and inaccuracy levels.
Findings
The effects on delivery schedule inaccuracies are contingent on a decoupling point, and a variable may have a combined amplifying (complexity generating) and stabilizing (complexity absorbing) moderating effect. Product complexity variables are significant regardless of the time horizon, and the item’s order life cycle is a significant variable with predictive differences that vary. Decoupling management is identified as a mechanism for generating complexity absorption capabilities contributing to delivery schedule accuracy.
Practical implications
The findings provide guidelines for exploring and finding patterns in specific variables to improve material delivery schedule inaccuracies and input into predictive forecasting models.
Originality/value
The findings contribute to explaining material delivery schedule variations, identifying potential root causes and moderators, empirically testing and validating effects and conceptualizing features that cause and moderate inaccuracies in relation to decoupling management and complexity theory literature?
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This paper aims at understanding how automotive firms integrate customer relationship management (CRM) tools and big data analytics (BDA) into their marketing strategies to…
Abstract
Purpose
This paper aims at understanding how automotive firms integrate customer relationship management (CRM) tools and big data analytics (BDA) into their marketing strategies to enhance total quality management (TQM) after the coronavirus disease (COVID-19).
Design/methodology/approach
A qualitative methodology based on a multiple-case study was adopted, involving the collection of 18 interviews with eight leading automotive firms and other companies responsible for their marketing and CRM activities.
Findings
Results highlight that, through the adoption of CRM technology, automotive firms have developed best practices that positively impact business performance and TQM, thereby strengthening their digital culture. The challenges in the implementation of CRM and BDA are also discussed.
Research limitations/implications
The study suffers from limitations related to the findings' generalizability due to the restricted number of firms operating in a single industry involved in the sample.
Practical implications
Findings suggest new relational approaches and opportunities for automotive companies deriving from the use of CRM and BDA under an overall customer-oriented approach.
Originality/value
This research analyzes how CRM and BDA improve the marketing and TQM processes in the automotive industry, which is undergoing deep transformation in the current context of digital transformation.
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Artemisa Ntourou and Aineas Mallios
The purpose of this paper is to assess the latest directives of the European Parliament and the Council – MiFID II and MiFIR – on markets in financial instruments in response to…
Abstract
Purpose
The purpose of this paper is to assess the latest directives of the European Parliament and the Council – MiFID II and MiFIR – on markets in financial instruments in response to the growth of dark pools in European equity markets.
Design/methodology/approach
This paper examines the impact of the new regulatory packages on European equity markets by identifying areas where the legislation is effective and comparing these changes in EU legislation with US legislation on dark pools.
Findings
This paper find that the MiFID II and MiFIR directives, implemented by the European Securities and Markets Authority to address these concerns, have reduced information asymmetry between market participants, thereby increasing competition between regulated markets and alternative trading facilities.
Research limitations/implications
Increased competition can improve market quality, which has practical implications for financial market regulation and policy formulation.
Originality/value
These findings are novel in the existing literature on high frequency trading through dark pools. They improve the understanding of dark trading and its impact on competition and market efficiency. In addition, this research can assist policymakers in designing effective financial market regulation. The economic analysis of legislation also helps regulators assess the impact of new legal provisions on the functioning of capital markets.
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Bingzi Jin, Xiaojie Xu and Yun Zhang
Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate…
Abstract
Purpose
Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.
Design/methodology/approach
The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.
Findings
A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.
Originality/value
The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.
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Stewart Clegg, Michael Grothe-Hammer and Kathia Serrano Velarde
This paper aims to conduct an experimental and theoretical investigation into fuel pre-delivery effects for a heavy fuel crankcase scavenged spark ignition two-stroke cycle engine…
Abstract
Purpose
This paper aims to conduct an experimental and theoretical investigation into fuel pre-delivery effects for a heavy fuel crankcase scavenged spark ignition two-stroke cycle engine for unmanned aerial vehicle application.
Design/methodology/approach
One-dimensional computational fluid dynamic modelling of the engine system using WAVE software supported by experimental dynamometer testing of the subject engine with kerosene JET A-1 and gasoline and fuels.
Findings
The experimental research has shown performance improvements using fuel preheating via use of auxiliary transfer port fuel injection. Computational simulation has allowed comparisons with auxiliary transfer port injection and direct in-cylinder injection to be made.
Practical implications
While some heavy fuel engines are now available for unmanned aerial vehicles the best solution to meet the military equipment single fuel policy remains an area of evolving research. The findings within this study show possibilities for fuel pre-treatment.
Originality/value
One-dimensional computational fluid dynamic modelling of the engine system using WAVE software supported by experimental dynamometer testing of the subject engine with kerosene JET A-1 and gasoline fuels.
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