Xiaoli Tang, Xiaolin Li and Zefeng Hao
Based on sensory marketing theory and cognitive appraisal theory, this study investigates whether and how the background visual complexity of live-streaming affects consumers'…
Abstract
Purpose
Based on sensory marketing theory and cognitive appraisal theory, this study investigates whether and how the background visual complexity of live-streaming affects consumers' purchase intention and reveals the underlying mechanisms through which background visual complexity influences consumers' purchase decisions.
Design/methodology/approach
The experiment was conducted with 180 college students, using eye-tracking technology to explore the impact mechanism of live background visual complexity on consumers' purchase intention, considering three types of background visual complexity (high vs medium vs low) and two levels of need for cognitive closure (high vs low).
Findings
Firstly, the background visual complexity of live-streaming positively influences consumers' purchase intention by eliciting positive emotions (pleasure and arousal), and the relationship between consumer emotions and purchase intention is nonlinear. Secondly, need for cognitive closure to significantly moderate the influence of background visual complexity on purchase intention.
Research limitations/implications
The limited sample size makes it difficult to generalize to other consumer groups. Also, the study only focuses on one visual factor, lacking comprehensive analysis from multiple perspectives.
Practical implications
It is recommended that live e-commerce companies optimize the visual design of live-streaming backgrounds and identify consumer traits to match the visual complexity with consumers' level of need for cognitive closure, thereby stimulating positive emotions and facilitating more satisfactory shopping decisions.
Originality/value
This paper addresses an interesting and practical issue related to the effects of live background visual complexity on consumers' purchase intention.
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Discusses an ongoing research work which attempts to formulate, develop and test mining equipment reliability assessment models based on genetic algorithms. Genetic algorithms are…
Abstract
Discusses an ongoing research work which attempts to formulate, develop and test mining equipment reliability assessment models based on genetic algorithms. Genetic algorithms are powerful and broadly applicable stochastic search techniques based on the principles of natural selection, heredity and genetics. The reason for selecting genetic algorithms is the fact that the reliability of mining equipment changes over time due to its dependence upon several covariates/factors (e.g. equipment age, the operating environment, number and quality of repairs). These factors combine to create a complex impact on an equipment’s reliability function. Gives an example of the application of genetic algorithms to capture the impact of these factors on time between failures of a piece of mining equipment.
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David N. Aratuo, Xiaoli L. Etienne, Tesfa Gebremedhin and David M. Fryson
The purpose of this study is to investigate the causal linkages between tourism and economic growth in the USA and determine how they respond to shocks in the system.
Abstract
Purpose
The purpose of this study is to investigate the causal linkages between tourism and economic growth in the USA and determine how they respond to shocks in the system.
Design/methodology/approach
The study uses a variety of time series procedures, including the bounds test, Granger causality test, impulse response functions and generalized variance decomposition to analyze the relationship between monthly tourist arrivals (TA) to the USA, real gross domestic product (GDP) and real effective exchange rates.
Findings
Results suggest that GDP Granger causes TA in the USA in the long run, indicating the economy-driven tourism growth hypothesis. Additionally, a shock to GDP generates a positive and significant effect on TA that persists in the long-run, while exchange rate shocks only have a significant effect in the first six months.
Research limitations/implications
Different tourism sectors may exert different degrees of influence on the economy. The use of aggregate data on TA in the analysis assumes homogeneity in the industry, thus, only represents the average relationship between tourism and GDP.
Practical implications
This study provides insight that shapes the investment, marketing, sustainability decisions of the public and private sectors aim at increasing tourist flows to drive economic development at the national, state and local levels.
Originality/value
Though several studies have examined the factors influencing the international tourist demand of the USA, this is the first to investigate the causal relationships between tourism, GDP and exchange rates for the USA. It is also the first in the US tourism literature to account for the nature of interactions between the three variables because of innovations in the system.
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Xiaoli Su, Lijun Zeng, Bo Shao and Binlong Lin
The production planning problem with fine-grained information has hardly been considered in practice. The purpose of this study is to investigate the data-driven production…
Abstract
Purpose
The production planning problem with fine-grained information has hardly been considered in practice. The purpose of this study is to investigate the data-driven production planning problem when a manufacturer can observe historical demand data with high-dimensional mixed-frequency features, which provides fine-grained information.
Design/methodology/approach
In this study, a two-step data-driven optimization model is proposed to examine production planning with the exploitation of mixed-frequency demand data is proposed. First, an Unrestricted MIxed DAta Sampling approach is proposed, which imposes Group LASSO Penalty (GP-U-MIDAS). The use of high frequency of massive demand information is analytically justified to significantly improve the predictive ability without sacrificing goodness-of-fit. Then, integrated with the GP-U-MIDAS approach, the authors develop a multiperiod production planning model with a rolling cycle. The performance is evaluated by forecasting outcomes, production planning decisions, service levels and total cost.
Findings
Numerical results show that the key variables influencing market demand can be completely recognized through the GP-U-MIDAS approach; in particular, the selected accuracy of crucial features exceeds 92%. Furthermore, the proposed approach performs well regarding both in-sample fitting and out-of-sample forecasting throughout most of the horizons. Taking the total cost and service level obtained under the actual demand as the benchmark, the mean values of both the service level and total cost differences are reduced. The mean deviations of the service level and total cost are reduced to less than 2.4%. This indicates that when faced with fluctuating demand, the manufacturer can adopt the proposed model to effectively manage total costs and experience an enhanced service level.
Originality/value
Compared with previous studies, the authors develop a two-step data-driven optimization model by directly incorporating a potentially large number of features; the model can help manufacturers effectively identify the key features of market demand, improve the accuracy of demand estimations and make informed production decisions. Moreover, demand forecasting and optimal production decisions behave robustly with shifting demand and different cost structures, which can provide manufacturers an excellent method for solving production planning problems under demand uncertainty.
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Lifan Chen, Shanshan Zhang, Xiaoli Hu, Shengming Liu and Rujia Lan
As a counterproductive interpersonal work behavior, knowledge hiding inhibits team creativity, hampers collaboration and ultimately has a detrimental impact on organizational…
Abstract
Purpose
As a counterproductive interpersonal work behavior, knowledge hiding inhibits team creativity, hampers collaboration and ultimately has a detrimental impact on organizational performance. Drawing upon the impression management perspective. This study aims to investigate how and when employees’ political skill affects their knowledge-hiding behavior in real work contexts.
Design/methodology/approach
The authors tested the hypotheses using data gathered from 266 employees in China using a time-lagged research design.
Findings
The results indicate that political skill positively influences knowledge hiding through the supplication strategy. Moreover, the positive effect of political skill on this strategy is stronger under higher levels of competition.
Research limitations/implications
A cross-sectional design and the use of self-report questionnaires are the limitations of this study.
Originality/value
The authors contribute to the literature on the emergence of knowledge hiding by identifying an impression management perspective. The authors also contribute to the literature on political skill by exploring the potential negative effects of political skill in the interpersonal interaction. Moreover, the authors enrich the understanding of the literature in competitive climate by introducing the impression management theory and exploring its influence on knowledge floating.
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Xiaoli Li, Zihan Peng and Kun Li
This study aims to explore the mechanism of boundary-spanning search on firm’s innovation performance under environmental dynamics from the perspective of strategic knowledge…
Abstract
Purpose
This study aims to explore the mechanism of boundary-spanning search on firm’s innovation performance under environmental dynamics from the perspective of strategic knowledge integration.
Design/methodology/approach
A survey was conducted among Chinese firm managers and R&D personnel, resulting in the collection of 315 valid samples. Hierarchical regression analysis was mainly adopted to demonstrate the hypothesized relationships, while the Sobel test and bootstrap method were used to further validate the mediating effects.
Findings
The results demonstrate that boundary-spanning search in different dimensions is a critical factor in the improvement of firm innovation performance (FIP). Two types of strategic knowledge integration are the main factors causing FIP and mediate the influence of boundary-spanning search on FIP. Furthermore, environmental dynamics moderate the relationship among boundary-spanning search, strategic knowledge integration and FIP.
Practical implications
Managers need to strengthen the boundary-spanning search for market and technical knowledge, which will promote firm innovative performance. Managers also need to implement strategic knowledge integration, which specifically includes using planned strategic knowledge integration to compensate for knowledge deficiencies, thereby achieving predetermined objectives; and using emergent strategic knowledge integration to update their understanding of internal and external environments, and to reset strategic objectives. In dynamic environments, managers should emphasize strategic knowledge management activities more.
Originality/value
From a strategic management perspective, this study categorizes strategic knowledge integration into planned and emergent forms. By applying the logic of knowledge acquisition, integration and creation, it explores how boundary-spanning search affects FIP through strategic knowledge integration as the intermediary and the boundary conditions of environmental dynamics. This not only provides a deeper understanding of the nature and effects of boundary-spanning research but also enhances the theory of strategic knowledge management.
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We aim to determine the subsidy mechanism that can help participants of green supply chain financing (GSCF) maximize their benefits. Then, the optimal subsidy mechanism is…
Abstract
Purpose
We aim to determine the subsidy mechanism that can help participants of green supply chain financing (GSCF) maximize their benefits. Then, the optimal subsidy mechanism is designed to promote the development of GSCF.
Design/methodology/approach
To better understand the impact of different government subsidy measures on the optimal strategy for GSCF, we treat the motivation of the participants in the supply chain as a cost–benefit decision-making process. Then, a Stackelberg game model is developed that accounts for consumers' green preferences and government subsidies. In addition, the factors influencing supply chain members' earnings are analyzed via computational experiments.
Findings
(1) When consumers 2019 green sensitivity reaches a certain threshold relative to that of core enterprises (CEs), the optimal order quantity of these enterprises is greater when the government subsidizes small and medium-sized enterprises (SMEs). Conversely, the optimal order quantity is greater when CEs are subsidized. (2) When the government subsidizes CEs, financial institutions (FIs) and SMEs at the same time, these forms of subsidies have a cumulative effect on the supply chain, and the supply chain and all participants generate the highest earnings.
Originality/value
We analyze the benefits of each participant of GSCF under different government subsidies and then determine the optimal subsidy measures.
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Lijuan Luo, Yuwei Wang, Siqi Duan, Shanshan Shang, Baojun Ma and Xiaoli Zhou
Based on the perspectives of social capital, image motivation and motivation affordances, this paper explores the direct and moderation effects of different kinds of motivations…
Abstract
Purpose
Based on the perspectives of social capital, image motivation and motivation affordances, this paper explores the direct and moderation effects of different kinds of motivations (i.e. relationship-based motivation, community-based motivation and individual-based motivation) on users' continuous knowledge contributions in social question and answer (Q&A) communities.
Design/methodology/approach
The authors collect the panel data of 10,193 users from a popular social Q&A community in China. Then, a negative binomial regression model is adopted to analyze the collected data.
Findings
The paper demonstrates that social learning, peer recognition and knowledge seeking positively affect users' continuous contribution behaviors. However, the results also show that social exposure has the opposite effect. In addition, self-presentation is found to moderate the influence of social factors on users' continuous use behaviors, while the moderation effect of motivation affordances has no significance.
Originality/value
First, this study develops a comprehensive motivation framework that helps gain deeper insights into the underlying mechanism of knowledge contribution in social Q&A communities. Second, this study conducts panel data analysis to capture the impacts of motivations over time, rather than intentions at a fixed time point. Third, the findings can help operators of social Q&A communities to optimize community norms and incentive mechanisms.
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Louma Ahmad Chaddad, Ali Chehab, Imad Elhajj and Ayman Kayssi
The purpose of this paper is to present an approach to reduce energy consumption in data centers. Subsequently, it reduces electricity bills and carbon dioxide footprints…
Abstract
Purpose
The purpose of this paper is to present an approach to reduce energy consumption in data centers. Subsequently, it reduces electricity bills and carbon dioxide footprints resulting from their use.
Design/methodology/approach
The authors present a mathematical model of the energy dissipation optimization problem. The authors formulate analytically the server selection problem and the supply air temperature as a non-linear programming, and propose an algorithm to solve it dynamically.
Findings
A simulation study on SimWare, using real workload traces, shows considerable savings for different data center sizes and utilization rates as compared to three other classic algorithms. The results prove that the proposed algorithm is efficient in handling the energy-performance trade-off, and that the proposed algorithm provides significant energy savings and maintains a relatively homogenous and stable thermal state at the different rack units in the data center.
Originality/value
The proposed algorithm ensures energy provisioning, performance optimization over existing state-of-the-art heuristics, and on-demand workload allocation.
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Guimei Wang, Shaohua Jin, Buqin Zhang, Fugui Yang and Xiaoli Ji
The coal reserves overlain by buildings, water bodies and railways are estimated to be about 14 billion tons in China. Based on the concept of green mining, in order to save the…
Abstract
The coal reserves overlain by buildings, water bodies and railways are estimated to be about 14 billion tons in China. Based on the concept of green mining, in order to save the unit energy, Double pumps in parallel forms of pumping are adopted in 0the paste filling of the pumping system. The optimal solution of the objective function could be obtained by taking the unit flow power of the pumping system as the objective function, using the quadratic polynomial by the least square method curve fitting and by the application of MATLAB. Thereby it is possible to reduce power consumption and increase the efficiency of the operating economy in the paste filling station.