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The purpose of this paper is to measure Chinese industries’ eco-efficiency during 2006-2013. The Chinese industry attained rapid achievement in recent decades, but meanwhile, overconsumption of energy and environmental pollution have become serious problems. To solve these problems, many research studies used the data envelopment analysis (DEA) to measure the Chinese industry’s eco-efficiency. However, because the target set by these works is usually the furthest one for a province to be efficient, it may hardly be accepted by any province.

This paper builds a new “closest target method” based on an additive DEA model considering the undesirable outputs. This method is a mixed-integer programming problem which can measure the ecological efficiency of provinces and more importantly guide the province to perform efficiently with minimum effort.

The results show that the eco-efficiency of Chinese provinces increased at the average level, but the deviations remained at a larger value. Compared to the “furthest” target methods, the targets by the approach proposed by this study are more acceptable for a province to improve its performance on both economy and environment counts.

This study is the first attempt to introduce the closest targets concept to measure the eco-efficiency and set the target for each provincial industry in China.

The purpose of this paper is to examine challenges and potential of big data in heterogeneous business networks and relate these to an implemented logistics solution.

The paper establishes an overview of challenges and opportunities of current significance in the area of big data, specifically in the context of transparency and processes in heterogeneous enterprise networks. Within this context, the paper presents how existing components and purpose-driven research were combined for a solution implemented in a nationwide network for less-than-truckload consignments.

Aside from providing an extended overview of today’s big data situation, the findings have shown that technical means and methods available today can comprise a feasible process transparency solution in a large heterogeneous network where legacy practices, reporting lags and incomplete data exist, yet processes are sensitive to inadequate policy changes.

The means introduced in the paper were found to be of utility value in improving process efficiency, transparency and planning in logistics networks. The particular system design choices in the presented solution allow an incremental introduction or evolution of resource handling practices, incorporating existing fragmentary, unstructured or tacit knowledge of experienced personnel into the theoretically founded overall concept.

The paper extends previous high-level view on the potential of big data, and presents new applied research and development results in a logistics application.

This paper aims to identify the impacts of wire and arc additive manufacturing (WAAM) technology on the green supply chain management (GSCM) performance. Also, it intends to identify the most essential WAAM capabilities.

An exploratory case study related to a metallurgical company using WAAM technology to repair metallic components was developed. A research framework to identify WAAM production capabilities and the different GSCM performance criteria was proposed based on the current state of the art. Primary qualitative data provided evidence for developing seven propositions relating WAAM capabilities to GSCM performance.

The paper provides empirical evidence relating to how WAAM production capabilities impact the different performance criteria of the GSCM performance. The results show that “relative advantage” and “supply-side benefits” are critical capabilities developed through WAAM. Furthermore, most of the capabilities regarding “relative advantage” and “supply-side benefits” promote a higher GSCM performance.

This research was carried out using a single case study research design and using qualitative data. Thus, future works are encouraged to test the propositions empirically using quantitative methodologies.

The case study findings support that most WAAM production capabilities promote a higher GSCM performance. Managers could use this research to understand the capabilities developed by this fusion-based additive manufacturing (AM), become aware of the implications of new technology adoption on the supply chain environmental externalities, and develop new business models based on the WAAM capabilities.

This research contributes to expanding the state-of-the art related to WAAM technology by evidencing the relationship between adopting this fusion-based AM technology and green supply chain practices. Also, it provides a set of seven propositions that could be used to theorise the impacts of WAAM adoption on the GSCM performance.

The purpose of this study is to describe the development of market based accounting research (MBAR) published in Indonesia for 10 years. This study attempts to explain the topics of MBAR, research method used, the variables, between-variable relationship formed, and the units analysis used in MBAR. This research uses qualitative-descriptive method to create descriptive models of MBAR articles published in accounting journals that have been accredited with minimum grade of B. The analysis of 109 MBAR articles of five accounting journals shows that 10 MBAR themes are still potential. Among three methods in MBAR, the multivariate association study is dominant. Some papers use intervening and moderating model to explore the relationship between accounting data and capital market reaction. The results for each theme are described in a research map that shows the relationship between variables (constructs) of MBAR from three units of analysis. This paper finds some implications to MBAR research agenda in the future, especially for meta-analysis research and triangulation research, due to many inconsistencies of the MBAR findings in Indonesia. In addition, accounting standard research topic is still promising in the moment of accounting standards transition.

The purpose of this paper is to build a novel data envelopment analysis (DEA) model to evaluate the efficiencies of decision making units (DMUs).

Using the Choquet integrals as aggregating tool, the authors give a novel DEA model to evaluate the efficiencies of DMUs.

It extends DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form. At last, the authors use the numerical examples to illustrate the performance of the proposed model.

The proposed DEA model can be used to evaluate the efficiency of the DMUs with multiple interactive inputs and outputs.

This paper introduce a new DEA model to evaluate the DMU with interactive variables (inputs or outputs), the classical DEA model is a special form.

Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the most appropriate AM technology can be challenging. This study aims to propose a method to solve the complex process selection in 3D printing applications, especially by creating a new multicriteria decision-making tool that takes the direct certainty of each comparison to reflect the decision-maker’s desire effectively.

The methodology proposed includes five steps: defining the AM technology selection decision criteria and constraints, extracting available AM parameters from the database, evaluating the selected AM technology parameters based on the proposed decision-making methodology, improving the accuracy of the decision by adopting newly proposed weighting scheme and selecting optimal AM technologies by integrating information gathered from the whole decision-making process.

To demonstrate the feasibility and reliability of the proposed methodology, this case study describes a detailed industrial application in rapid investment casting that applies the weightings to a tailored AM technologies and materials database to determine the most suitable AM process. The results showed that the proposed methodology could solve complicated AM process selection problems at both the design and manufacturing stages.

This research proposes a unique multicriteria decision-making solution, which employs an exclusive weightings calculation algorithm that converts the decision-maker's subjective priority of the involved criteria into comparable values. The proposed framework can reduce decision-maker's comparison duty and potentially reduce errors in the pairwise comparisons used in other decision-making methodologies.

Through this research study, the authors found that digital thread has made significant progress in the life cycle management of the US Air Force. The authors hope that by reviewing similar studies in the aerospace field, the meaning of digital thread can be summarized and applied to a wider range of fields. In addition, theoretically, the definition of digital twin and digital thread are not unified. The authors hope that the comparison of digital thread and digital twin will better enable scholars to distinguish between the two concepts. Besides, the authors are also looking forward that more people will realize the significance of digital thread and carry out future research.

Complete research about digital thread and the relevant concept of the digital twin is conducted. First, by searching in Google Scholar with the keyword “digital thread”, the authors filter results and save literature with high relevance to digital thread. The authors also track these papers’ references for more paper of digital thread and digital twin. After removing the duplicate and low-relevance literature, 72 digital thread-related literature studies are saved and further analyzed from the perspective of time development, application field and research directions.

Digital thread application in industries other than the aviation manufacturing industry is still relatively few, and the research on the application of digital thread in real industrial scenarios is mainly at the stage of framework design and design-side decision optimization. In addition, the digital thread needs a new management mechanism and organizational structure to realize landing. The new management mechanism and the process can adapt to the whole life cycle management process based on the digital thread, manage the data security and data update, and promote the digital thread to play a better effect on the organizational management.

Based on a review of digital thread, future research directions and usage suggestions are given. The fault diagnosis of high-speed train bogie as an example shows the effectiveness of the method and also partially demonstrates the advantages and effects brought by the digital thread connecting the data models at various stages.

This paper first investigates and analyzes the theoretical connotation and research progress of digital thread and gives a complete definition of digital thread from the perspective of the combination of digital thread and digital twins. Next, the research process of digital thread is reviewed, and the application fields, research directions and achievements in recent years are summarized. Finally, taking the fault diagnosis of high-speed train bogie as an example partially demonstrates the advantages and effects brought by the digital thread connecting the data models at various stages.

This research's main objective is to investigate the relationship between consumption expenditure and consumer confidence in the USA and to study their effects on US economic revivalism during and after the coronavirus disease 2019 (COVID-19) shock.

The authors use Michigan's monthly Consumer Sentiment Index and its five components from January 1978 to April 2020. The study is unique in quantifying the potential variations in US consumer confidence due to COVID-19 under different scenarios, by providing a projection until December 2021. It also estimates the time needed for recovery and offers guidance to policymakers on ways to contain the negative impacts of COVID-19 on the economy by restoring consumer confidence.

All scenarios show a gradual recovery of consumer confidence and consumption expenditure. This study recommends expansionary policies to encourage consumption expenditure to generate additional demand and boost economic growth and job creation.

Though this study is limited to the US consumer confidence index, it offers significant implications for marketers, customers and policymakers of other developed economies. The authors recommend expansionary economic policies to boost consumer confidence, raise economic growth and result in job creation.

The study is unique in quantifying the potential variations in US consumer confidence due to COVID-19 under different scenarios; by providing a projection until December 2021. It also estimates the time needed for recovery and guidance for policymakers on ways to contain the COVID-19 shock negative impacts on the economy by restoring consumer confidence.

An inclusive financial system is essential to develop the country’s economy. A massive shift in financial inclusion was observed by the initiative of government to include financially excluded into the formal financial system by launching Pradhan Mantri Jan Dhan Yojana (PMJDY) in 2014. This paper aims to attempt to examine the efficiency of public sector banks in financial inclusion during pre and post introduction of PMJDY.

The data envelopment analysis is used to measure the efficiency of the banks towards financial inclusion for the periods, 2010–2011 to 2013–2014 as pre-introduction and 2014–2015 to 2017–2018 as post-introduction phase. For this study, supply-side parameters of financial inclusion considered as input variables and demand-side parameters as output variables.

The study finds that overall average efficiency towards financial inclusion increases significantly during post-phase, though all the public sector banks are not performing equally. There is a significant variation in efficiency level between them and even between the two periods. Further, there is a huge opportunity to enhance technical efficiency with the same quantity of input which will help to achieve the target of financial inclusion.

A comparative study between the two phases has taken place to analyse the impact of the scheme on the technical efficiency of banks. One of the notable innovativeness of this study is that, unlike most of the previous studies which are mostly theoretical and conceptual, the present study may place itself as a unique inquiry in the domain of efficiency review of public sector banks during pre and post introduction of PMJDY.

Multipath routing holds a great potential to provide sufficient bandwidth to a plethora of applications in wireless sensor networks. In this paper, we consider the problem of interference that can significantly affect the expected performances. We focus on the performance evaluation of the iterative paths discovery approach as opposed to the traditional concurrent multipath routing. Five different variants of multipath protocols are simulated and evaluated using different performance metrics. We mainly show that the iterative approach allows better performances when used jointly with an interference-aware metric or when an interference-zone marking strategy is employed. This latter appears to exhibit the best performances in terms of success ratio, achieved throughput, control messages overhead as well as energy consumption.