Jiaxin Wu, Lei Liu and Hongjuan Yang
This study aims to evaluate the characteristics of climate change in Yunnan minority areas and identify an effective path to promote sustainable livelihoods based on climate…
Abstract
Purpose
This study aims to evaluate the characteristics of climate change in Yunnan minority areas and identify an effective path to promote sustainable livelihoods based on climate change.
Design/methodology/approach
Taking Yunnan Province as an example, based on the expansion of the traditional sustainable livelihood framework, the authors constructed a system dynamics (SD) model of sustainable livelihood from the six subsystems of natural, physical, financial, social, human and cultural and tested the accuracy and effectiveness of the model with data from Cangyuan County. By adjusting these parameters, five development paths are designed to simulate the future situation of the livelihood system and determine the optimal path.
Findings
Climate change has exacerbated the vulnerability of people’s livelihoods. In future, each of the five development paths will be advantageous for promoting sustainable livelihoods. However, compared with Path I (maintaining the status quo), Path III (path of giving priority to culture) and Path IV (path of giving priority to economic development) have more obvious advantages. Path II (path of giving priority to people’s lives) gradually increases the development rate by promoting people’s endogenous motivation, and Path V (path of coordinated development) is better than the other paths because of its more balanced consideration.
Originality/value
The analytical framework of sustainable livelihoods based on the characteristics of minority areas is broadened. By constructing a SD model of the livelihood system, the limitations of traditional static analysis have been overcome and a development path for promoting sustainable livelihoods through simulation is proposed. This study offers a theoretical framework and reference method for livelihood research against the backdrop of climate change and a decision-making basis for enhancing climate adaptability and realizing sustainable livelihoods.
Details
Keywords
Shipeng Wang, Lizhen Cui, Lei Liu, Xudong Lu and Qingzhong Li
The purpose of this paper is to build cyber-physical-psychological ternary fusion crowd intelligence network and realize comprehensive, real, correct and synchronous projection in…
Abstract
Purpose
The purpose of this paper is to build cyber-physical-psychological ternary fusion crowd intelligence network and realize comprehensive, real, correct and synchronous projection in cyber–physical–psychological ternary fusion system. Since the network of crowd intelligence is the future interconnected network system that takes on the features of large scale, openness and self-organization. The Digital-selfs in the network of crowd intelligence interact and cooperate with each other to finish transactions and achieve co-evolution eventually.
Design/methodology/approach
To realize comprehensive, real, correct and synchronous projection between cyber–physical–psychological ternary fusion system, the authors propose the rules and methods of projection from real world to the CrowdIntell Network. They build the mental model of the Digital-self including structure model and behavior model in four aspects: identity, provision, demand and connection, thus forming a theoretical mental model framework of Digital-self.
Findings
The mental model is excepted to lay a foundation for the theory of modeling and simulation in the research of crowd science and engineering.
Originality/value
This paper is the first one to propose the mental model framework and projection rules and methods of Digital-selfs in network of crowd intelligence, which lays a solid foundation for the theory of modeling, simulation, intelligent transactions, evolution and stability of CrowdIntell Network system, thus promoting the development of crowd science and engineering.
Details
Keywords
Lizhen Cui, Xudong Zhao, Lei Liu, Han Yu and Yuan Miao
Allocation of complex crowdsourcing tasks, which typically include heterogeneous attributes such as value, difficulty, skill required, effort required and deadline, is still a…
Abstract
Purpose
Allocation of complex crowdsourcing tasks, which typically include heterogeneous attributes such as value, difficulty, skill required, effort required and deadline, is still a challenging open problem. In recent years, agent-based crowdsourcing approaches focusing on recommendations or incentives have emerged to dynamically match workers with diverse characteristics to tasks to achieve high collective productivity. However, existing approaches are mostly designed based on expert knowledge grounded in well-established theoretical frameworks. They often fail to leverage on user-generated data to capture the complex interaction of crowdsourcing participants’ behaviours. This paper aims to address this challenge.
Design/methodology/approach
The paper proposes a policy network plus reputation network (PNRN) approach which combines supervised learning and reinforcement learning to imitate human task allocation strategies which beat artificial intelligence strategies in this large-scale empirical study. The proposed approach incorporates a policy network for the selection of task allocation strategies and a reputation network for calculating the trends of worker reputation fluctuations. Then, by iteratively applying the policy network and reputation network, a multi-round allocation strategy is proposed.
Findings
PNRN has been trained and evaluated using a large-scale real human task allocation strategy data set derived from the Agile Manager game with close to 500,000 decision records from 1,144 players in over 9,000 game sessions. Extensive experiments demonstrate the validity and efficiency of computational complex crowdsourcing task allocation strategy learned from human participants.
Originality/value
The paper can give a better task allocation strategy in the crowdsourcing systems.
Details
Keywords
Pengze Li, Ran Zhang, Lei Liu, Lizhen Cui, Qingzhong Li and Guangpeng Zhou
Science of the Crowd is a new paradigm. The research on the relationship between provision and requirement arising from the behavior of the crowd under the interconnected…
Abstract
Purpose
Science of the Crowd is a new paradigm. The research on the relationship between provision and requirement arising from the behavior of the crowd under the interconnected environment is a promising topic. This paper aims at studying a new type of interconnected architecture.
Design/methodology/approach
This study is a pioneer work on the establishment of a new type of interconnected architecture – rim chain. The rim chain aims at supporting prompt matching between provision and requirements.
Findings
The analytical results suggest that requirements can be fulfilled in accordance with six degrees of separation. In other words, the matching between the requirements and provision takes place with six hops in the rim chain framework.
Originality/value
Knowledge graph is used to implement the rim chain.
Details
Keywords
Hongping Xing, Yu Liu and Xiaodan Sun
The smoothness of the high-speed railway (HSR) on the bridge may exceed the allowable standard when an earthquake causes vibrations for HSR bridges, which may threaten the safety…
Abstract
Purpose
The smoothness of the high-speed railway (HSR) on the bridge may exceed the allowable standard when an earthquake causes vibrations for HSR bridges, which may threaten the safety of running trains. Indeed, few studies have evaluated the exceeding probability of rail displacement exceeding the allowable standard. The purposes of this article are to provide a method for investigating the exceeding probability of the rail displacement of HSRs under seismic excitation and to calculate the exceeding probability.
Design/methodology/approach
In order to investigate the exceeding probability of the rail displacement under different seismic excitations, the workflow of analyzing the smoothness of the rail based on incremental dynamic analysis (IDA) is proposed, and the intensity measure and limit state for the exceeding probability analysis of HSRs are defined. Then a finite element model (FEM) of an assumed HSR track-bridge system is constructed, which comprises a five-span simply-supported girder bridge supporting a finite length CRTS II ballastless track. Under different seismic excitations, the seismic displacement response of the rail is calculated; the character of the rail displacement is analyzed; and the exceeding probability of the rail vertical displacement exceeding the allowable standard (2mm) is investigated.
Findings
The results show that: (1) The bridge-abutment joint position may form a step-like under seismic excitation, threatening the running safety of high-speed trains under seismic excitations, and the rail displacements at mid-span positions are bigger than that at other positions on the bridge. (2) The exceeding probability of rail displacement is up to about 44% when PGA = 0.01g, which is the level-five risk probability and can be described as 'very likely to happen'. (3) The exceeding probability of the rail at the mid-span positions is bigger than that above other positions of the bridge, and the mid-span positions of the track-bridge system above the bridge may be the most hazardous area for the running safety of trains under seismic excitation when high-speed trains run on bridges.
Originality/value
The work extends the seismic hazardous analysis of HSRs and would lead to a better understanding of the exceeding probability for the rail of HSRs under seismic excitations and better references for the alert of the HSR operation.
Details
Keywords
Maria Romero-Charneco, Ana-María Casado-Molina, Pilar Alarcón-Urbistondo and Juan Pedro Cabrera Sánchez
Given the importance of chatbots in customer service in tourism, this paper aims to understand the drivers that predispose regular consumers of restaurant recommendation chatbots…
Abstract
Purpose
Given the importance of chatbots in customer service in tourism, this paper aims to understand the drivers that predispose regular consumers of restaurant recommendation chatbots to continue using them.
Design/methodology/approach
A total of 386 regular consumers of a chatbot via WhatsApp restaurant recommender responded to an online questionnaire (inspired by scales found in the literature on technology adoption). Structural equation modeling was used to test the hypotheses.
Findings
Significant predictors of intention to continue using these chatbots included “effort expectancy (EE),” “hedonic motivation (HM),” “price value (PV)” and “habit (HT).” Specifically, HT still has a long way to go in terms of its performance, and it will be possible to work on it. Furthermore, two variables, EE and HM, act as a bottleneck when it comes to explaining this recurrent usage intention. Factors such as “performance expectancy (PE),” “facilitating conditions (FC)” and “social influence (SI)” did not influence “behavioral intention (BI).” Likewise, the moderating variables, age and gender, are not significant. Finally, the predictive capability of the model is demonstrated. The study findings will enable the development of effective strategies to foster consumer loyalty to this new technology in the restaurant industry.
Originality/value
This study contributes, building on the suitability of the unified theory of acceptance and use of technology 2 model, to explain users’ intention to continue using chatbot tourism services in the context of an information search for an unplanned and varied purchase decision, namely, restaurant recommendation services. To the best of the authors’ knowledge, this is the first analysis of tourist’s intention to reuse a real and fully functional chatbot via mobile instant messaging.
研究目的
鉴于聊天机器人在旅游客户服务中的重要性, 本研究旨在了解驱动消费者持续使用WhatsApp餐厅推荐聊天机器人的因素。
研究方法
共收集386名WhatsApp餐厅推荐聊天机器人的常规用户在线问卷数据(问卷设计参考技术采纳相关文献中的量表)。研究采用结构方程模型(SEM)验证假设。
研究发现
影响用户持续使用意图的显著预测因素包括“努力期望(EE)”、“享乐动机(HM)”、“价格价值(PV)”和“习惯(HT)”。其中, “习惯(HT)”表现仍有提升空间, 而“努力期望(EE)”和“享乐动机(HM)”是解释持续使用意图的瓶颈因素。此外, “绩效期望(PE)”、“促进条件(FC)”和“社会影响(SI)”对“行为意图(BI)”无显著影响。性别和年龄等调节变量同样不显著。研究结果验证了模型的预测能力, 能够为餐厅行业制定有效策略以增强消费者对这一新技术的忠诚度提供指导。
研究创新
本研究基于UTAUT2模型, 首次分析了消费者在餐厅推荐服务中持续使用移动即时通讯(MIM)聊天机器人的意图, 为探索非计划性和多样化购买决策背景下的信息搜索服务提供了新见解。
Details
Keywords
Jianran Liu and Wen Ji
In recent years, with the increase in computing power, artificial intelligence can gradually be regarded as intelligent agents and interact with humans, this interactive network…
Abstract
Purpose
In recent years, with the increase in computing power, artificial intelligence can gradually be regarded as intelligent agents and interact with humans, this interactive network has become increasingly complex. Therefore, it is necessary to model and analyze this complex interactive network. This paper aims to model and demonstrate the evolution of crowd intelligence using visual complex networks.
Design/methodology/approach
This paper uses the complex network to model and observe the collaborative evolution behavior and self-organizing system of crowd intelligence.
Findings
The authors use the complex network to construct the cooperative behavior and self-organizing system in crowd intelligence. Determine the evolution mode of the node by constructing the interactive relationship between nodes and observe the global evolution state through the force layout.
Practical implications
The simulation results show that the state evolution map can effectively simulate the distribution, interaction and evolution of crowd intelligence through force layout and the intelligent agents’ link mode the authors proposed.
Originality/value
Based on the complex network, this paper constructs the interactive behavior and organization system in crowd intelligence and visualizes the evolution process.
Details
Keywords
Hong Jiang, Jingxuan Yang and Wentao Liu
This study aims to explore the effect of innovation ecosystem stability (IES) on innovation performance of enterprises through the mediating role of knowledge acquisition (KA)…
Abstract
Purpose
This study aims to explore the effect of innovation ecosystem stability (IES) on innovation performance of enterprises through the mediating role of knowledge acquisition (KA), and to study how these effects are moderated by unabsorbed slack.
Design/methodology/approach
This study draws on data from 327 Chinese enterprises and adopts the multiple linear regression method and bootstrapping method to explore the mediating effect of KA and its moderated mediating effect.
Findings
The results demonstrate that IES is positively associated with innovation performance of enterprises, and KA plays a partially mediating role. Moreover, unabsorbed slack negatively moderates the relationship between IES and KA as well as the mediating effect of KA.
Originality/value
This study investigates the relationship between IES and innovation performance, and the mechanism of influence, which has not been previously studied in the field of innovation ecosystem. This study also examines the interaction between unabsorbed slack and IES and further clarifies the mechanism and boundary conditions of the impact of IES on innovation performance.
Details
Keywords
Joanna Grochowalska, Piotr Jaworski, Łukasz Jan Kapusta and Jerzy Kowalski
In the cylinders of a marine diesel engine, self-ignition occurs in a very short time after the fuel injection into the combustion chamber. Therefore, this paper aims to develop a…
Abstract
Purpose
In the cylinders of a marine diesel engine, self-ignition occurs in a very short time after the fuel injection into the combustion chamber. Therefore, this paper aims to develop a model of diesel fuel spray for the early stage of fuel spray in the marine diesel engine. The main technical aspects such as nozzle diameter of the marine engine injector and backpressure in the combustion chamber were taken into consideration.
Design/methodology/approach
In this paper, laboratory experimental studies were carried out to determine parameters of fuel spray in an early stage of injection in the marine diesel engine. The optical measuring Mie scattering technique was used to record the fuel injection process. The working space was a constant volume chamber. The backpressure parameters in the constant volume chamber were the same as during the operation of the marine diesel engine. Based on the experimental studies and important Hiroyasu and Arai models of fuel spray presented in literature was proposed new model of fuel spray parameters for marine diesel injectors.
Findings
In this paper, the proposed new model of the two main parameters described fuel spray evolution”: new model of spray tip penetration (STP) and spray cone angle (SCA). New model propagation of fuel STP in time was included the influence of nozzle diameter and backpressure. The proposed model has a lower error, about 15%–34%, than the model of Hiroyasu and Arai. Moreover, a new model of the evolution over time of the SCA is developed.
Research limitations/implications
In the future research of fuel spray process must be taken influence of the fuel temperature. Diesel fuel has a different density and viscosity in dependence of fuel temperature. Therefore are predicted of the expansion about influence of fuel temperature, new model of fuel spray for a marine diesel engine. The main limitations occurring in the research are not possible to carry out the research while real operation marine diesel engine.
Originality/value
An experimental test was carried out for a real fuel injector of a marine diesel engine. Design parameters and fuel injection parameters were selected on the basis of the actual one. In the literature, SCA is defined as a constant parameter for the specific preliminary data. A new model for the early stage of fuel spray of SCA propagation in time has been proposed. The early stage of fuel spray is especially important, because in this time comes in there to fuel self-ignition.
Details
Keywords
Noura AlNuaimi, Mohammad Mehedy Masud, Mohamed Adel Serhani and Nazar Zaki
Organizations in many domains generate a considerable amount of heterogeneous data every day. Such data can be processed to enhance these organizations’ decisions in real time…
Abstract
Organizations in many domains generate a considerable amount of heterogeneous data every day. Such data can be processed to enhance these organizations’ decisions in real time. However, storing and processing large and varied datasets (known as big data) is challenging to do in real time. In machine learning, streaming feature selection has always been considered a superior technique for selecting the relevant subset features from highly dimensional data and thus reducing learning complexity. In the relevant literature, streaming feature selection refers to the features that arrive consecutively over time; despite a lack of exact figure on the number of features, numbers of instances are well-established. Many scholars in the field have proposed streaming-feature-selection algorithms in attempts to find the proper solution to this problem. This paper presents an exhaustive and methodological introduction of these techniques. This study provides a review of the traditional feature-selection algorithms and then scrutinizes the current algorithms that use streaming feature selection to determine their strengths and weaknesses. The survey also sheds light on the ongoing challenges in big-data research.