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Sharding of blockchains consists of partitioning a blockchain network into several sub-networks called “shards,” each shard processing and storing disjoint sets of transactions in parallel. Sharding has recently been applied to public blockchains to improve scalability through parallelism. The throughput of sharded blockchain is optimized when the workload among the shards is approximately the same. The purpose of this paper is to investigate the problem of balancing workload of account-based blockchains such as Ethereum.

Two known consensus-based distributed load-balancing algorithms have been adapted to sharded blockchains. These algorithms migrate accounts across shards to balance transaction processing times. Two methods to predict transaction processing times are proposed.

The authors identify some challenging aspects for solving the load-balancing problem in sharded blockchains. Experiments conducted with Ethereum transactions show that the two load-balancing algorithms are challenged by accounts often created to process a single transaction to optimize anonymity, while existing accounts sparsely generate transactions.

Tests in this work have been conducted on transactions originating from a blockchain platform rather than using artificially generated data distributions. They show the specificity of the load-balancing problem for sharded blockchains, which were hidden in artificial data sets.

This review aims to give a critical view of the wheel/rail high frequency vibration-induced vibration fatigue in railway bogie.

Vibration fatigue of railway bogie arising from the wheel/rail high frequency vibration has become the main concern of railway operators. Previous reviews usually focused on the formation mechanism of wheel/rail high frequency vibration. This paper thus gives a critical review of the vibration fatigue of railway bogie owing to the short-pitch irregularities-induced high frequency vibration, including a brief introduction of short-pitch irregularities, associated high frequency vibration in railway bogie, typical vibration fatigue failure cases of railway bogie and methodologies used for the assessment of vibration fatigue and research gaps.

The results showed that the resulting excitation frequencies of short-pitch irregularity vary substantially due to different track types and formation mechanisms. The axle box-mounted components are much more vulnerable to vibration fatigue compared with other components. The wheel polygonal wear and rail corrugation-induced high frequency vibration is the main driving force of fatigue failure, and the fatigue crack usually initiates from the defect of the weld seam. Vibration spectrum for attachments of railway bogie defined in the standard underestimates the vibration level arising from the short-pitch irregularities. The current investigations on vibration fatigue mainly focus on the methods to improve the accuracy of fatigue damage assessment, and a systematical design method for vibration fatigue remains a huge gap to improve the survival probability when the rail vehicle is subjected to vibration fatigue.

The research can facilitate the development of a new methodology to improve the fatigue life of railway vehicles when subjected to wheel/rail high frequency vibration.

Purpose: To outline recent developments in digital service delivery in order to encourage researchers to pursue collaborations with computer science, operations research, and data science colleagues and to show how such collaborations can expand the scope of research on emotion in service delivery.

Design/methodology/approach: Uses archived resources available at http://LivePerson.com to extract data based in genuine service conversations between agents and customers. We refer to these as “digital traces” and analyze them using computational science models.

Findings: Although we do not test significance or causality, the data presented in this chapter provide a unique lens into the dynamics of emotions in service; results that are not obtainable using traditional research methods.

Research limitations/implications: This is a descriptive study where findings unravel new dynamics that should be followed up with more research, both research using traditional experimental methods, and digital traces research that allows inferences of causality.

Practical implications: The digital data and newly developed tools for sentiment analyses allow exploration of emotions in large samples of genuine customer service interactions. The research provides objective, unobtrusive views of customer emotions that draw directly from customer expressions, with no self-report intervention and biases.

Originality/value: This is the first objective and detailed depiction of the actual emotional encounters that customers express, and the first to analyze in detail the nature and content of customer service work.

This review paper aims to focus on recent advances of carbon nanotubes (CNTs) to produce gas sensors. Gas sensors are widely used for monitoring hazardous gas leakages and emissions in the industry, households and other areas. For better safety and a healthy environment, it is highly desirable to have gas sensors with higher accuracy and enhanced sensing features.

In this review, the authors focus on recent contributions of CNTs to the technology for developing different types of gas sensors. The design, fabrication process and sensing mechanism of each gas sensor are summarized, together with their advantages and disadvantages.

Nowadays, CNTs are well-known materials which have attracted a significant amount of attention owing to their excellent electrical, electronic and mechanical properties. On exposure to various gases, their properties allow the detection of gases using different methods. Therefore, over recent years, researchers have developed several different types of gas sensors along with other types of sensors for temperature, strain, pressure, etc.

The main purpose of this review is to introduce CNTs as candidates for future research in the field of gas sensing applications and to focus on current technical challenges associated with CNT-based gas sensors.

Smartphone apps collect users' personal information, which triggers privacy concerns for app users. Consequently, app users restrict apps from accessing their personal information. This may impact the effectiveness of in-app advertising. However, research has not yet demonstrated what factors impact app users' decisions to use apps with restricted permissions. This study is aimed to bridge this gap.

Using a quantitative research method, the authors collected the data from 384 app users via a structured questionnaire. The data were analysed using AMOS and fuzzy-set qualitative comparative analysis (fsQCA).

The findings suggest privacy concerns and risks have a significant positive effect on app usage with restricted permissions, whilst reputation, trust and perceived benefits have significant negative impact on it. Some app-related factors, such as the number of apps installed and type of apps, also impact app usage with restricted permissions.

Based on the findings, the authors provided several implications for app stores, app developers and app marketers.

This study examines the factors that influence smartphone users' decisions to use apps with restricted permission requests. By doing this, the authors' study contributes to the consumer behaviour literature in the context of smartphone app usage. Also, by explaining the underlying mechanisms through which the principles of communication privacy management theory operate in smartphone app context, the authors' research contributes to the communication privacy management theory.

In the process of group decision-making, there may be multilayer subjects. In other words, members of the decision-making group may come from different layers and there is interest game among decision experts. Therefore, it is an extremely important topic to aggregate the information of decision experts who are involved in hierarchical relations and gaming relations so as to effectively address game conflicts and reach game cooperation.

First, a programming model is established to minimize the difference of expert opinions in hierarchical decision-making, and the method to solve the optimal solution is given. Second, the cooperative game model and its properties are discussed by using cooperative game and Shapley value, and the method to determine the weight vector between layers is also proposed.

This model can quickly aggregate information and achieve game equilibrium among decision-makers with hierarchical relationships. It can be widely used in decision evaluation with hierarchy structure and has certain practical value.

In order to solve the problem that experts at different levels may have conflicts of interest in multilayer grey situation group decision-making process, cooperative game and Shapley value theory are introduced into the study, and a multilayer grey situation group decision-making model based on cooperative game is constructed. The validity and practicability of the model are illustrated by an example.

This paper aims to examine how mortality-related sadness, as compared to other emotions such as fear, anger and happiness, can leverage the effectiveness of fresh start appeals.

Drawing upon the consumption-based affect regulation principle, this paper investigates how sadness associated with mortality can elicit the appraisal of irretrievable loss, which subsequently increases the effectiveness of fresh start appeals. These predictions are tested across three experimental studies.

Findings demonstrate that mortality-related sadness enhances donation allocations (Study 1), willingness to pay (Study 2) and favorable attitudes (Study 3) toward an advertisement promoted with a fresh start appeal. This effect is mediated by an appraisal of irretrievable loss (Studies 1–3). Moreover, the emotion’s effect only emerges among consumers who believe that their emotional experiences are stable (vs malleable) (Study 3).

This paper investigates the effects of negative (vs positive emotions). It would thus be of interest to explore whether different discrete positive emotions may also enhance favorable evaluations of fresh start appeals.

While fresh start appeals have been widely used by marketers and organizations, the extant literature in this area has yet to identify how marketers can leverage the effectiveness of such appeals. This paper highlights how a specific negative emotion can be beneficial to marketers in leveraging the effectiveness of fresh start appeals.

The findings of this research suggest a novel potential strategy for the regulation of sadness. Specifically, consumers experiencing mortality-related sadness show favorable evaluations of fresh start appeals, indicating they are seeking to dissociate themselves from the past.

This work aims to investigate the sensitivity of ranking performance with respect to the topic distribution of queries selected for ranking evaluation.

The authors reweight queries used in two TREC tasks to make them match three real background topic distributions, and show that the performance rankings of retrieval systems are quite different.

It is found that search engines tend to perform similarly on queries about the same topic; and search engine performance is sensitive to the topic distribution of queries used in evaluation.

Using experiments with multiple real‐world query logs, the paper demonstrates weaknesses in the current evaluation model of retrieval systems.

Many managers and scholars focus on how to repair brand image after a corporate crisis. This research paper aims to propose that a fresh start mindset (FSM) and brand crisis type can jointly influence consumer forgiveness.

Three studies were conducted to examine the authors’ hypotheses. Study 1 is a 3 (FSM: high vs low vs control) × 2 (brand crisis: controllable vs uncontrollable) between-subjects factorial design to test the interaction effect of FSM and brand crisis type on consumer forgiveness. Study 2 is a 2 (FSM: high vs low) × 2 (brand crisis: controllable vs uncontrollable) between-subjects factorial design to identify the affective and cognitive mechanisms in the influence of FSM and brand crisis type on consumer forgiveness. Study 3 is a 2 (FSM: high vs low) × 2 (brand crisis: controllable vs uncontrollable) × 3 (strategy: defensive strategy vs accommodative strategy vs reticence) between-subjects factorial design, aimed to identify the possible boundary conditions of this effect and tested the moderating role of brand crisis response strategies.

Study 1 finds that the FSM interacts with brand crisis type to affect consumer forgiveness. Specifically, consumers faced with uncontrollable (vs controllable) brand crises tend to increase (vs decrease) consumer forgiveness after a corporate crisis. Study 2 identifies the underlying mechanism, such that two distinct mechanisms drive the interaction effect. Affective empathy and perceived responsibility mediate the interaction effect of FSM and brand crisis type on forgiveness. Study 3 replicates the findings of studies 1 and 2 and confirms the boundary condition of the effect, showing that crisis response strategy moderates the interaction between FSM and brand crisis type.

Theoretically, to the best of the authors’ knowledge, this research observes the interactive effect of FSM and brand crisis for the first time, thus extending the existing research on both FSM and brand crisis. This study also enriches existing empathy and responsibility literature by examining the mediating role of empathy and perceived responsibility. Practical implications for marketers are apparent, especially after a brand crisis occurs. Corporates can deal with different types of the brand crisis based on consumers’ FSM. Finally, future research with regards to the findings is discussed.

Purpose – The advancement of multimedia technology has spurred the use of multimedia in business practice. The adoption of audio and visual data will accelerate as marketing scholars become more aware of the value of audio and visual data and the technologies required to reveal insights into marketing problems. This chapter aims to introduce marketing scholars into this field of research.Design/methodology/approach – This chapter reviews the current technology in audio and visual data analysis and discusses rewarding research opportunities in marketing using these data.Findings – Compared with traditional data like survey and scanner data, audio and visual data provides richer information and is easier to collect. Given these superiority, data availability, feasibility of storage, and increasing computational power, we believe that these data will contribute to better marketing practices with the help of marketing scholars in the near future.Practical implications: The adoption of audio and visual data in marketing practices will help practitioners to get better insights into marketing problems and thus make better decisions.Value/originality – This chapter makes first attempt in the marketing literature to review the current technology in audio and visual data analysis and proposes promising applications of such technology. We hope it will inspire scholars to utilize audio and visual data in marketing research.