Hedonic value is commonly conceded as a determinant of behavioral intentions toward location-based advertising (LBA). However, the careful consideration of a mechanism behind…
Abstract
Purpose
Hedonic value is commonly conceded as a determinant of behavioral intentions toward location-based advertising (LBA). However, the careful consideration of a mechanism behind hedonic motivation and its subsequent impact on continuance intention is inadequate. This study aims to explore the formation of hedonic value and its motivation for prolonged usage toward LBA.
Design/methodology/approach
A sample of 486 mobile users was recruited to evaluate the research model using structural equation modeling (SEM).
Findings
Results reveal that perceived utility and promotional offers are the strongest indicators of hedonic value. Moreover, social support and contextual convenience play an essential role in heightening hedonic value. Furthermore, the research lenses attempt to clarify the direct, indirect influences of hedonic value, irritation and perceived credibility on continuance intention.
Practical implications
The findings offer practitioners an understanding of how to improve hedonic value and continuance intention and develop effective LBA strategies in emerging markets.
Originality/value
This study narrows the gap of current literature by formulating a hedonic value-based continuance intention model based on uses and gratifications theory (UGT). Additionally, this work illuminates the insights into hedonic value toward LBA by identifying its motivations, including perceived utility, promotional offers, social support and contextual convenience.
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Quan Yuan, Xuecai Xu, Tao Wang and Yuzhi Chen
This study aims to investigate the safety and liability of autonomous vehicles (AVs), and identify the contributing factors quantitatively so as to provide potential insights on…
Abstract
Purpose
This study aims to investigate the safety and liability of autonomous vehicles (AVs), and identify the contributing factors quantitatively so as to provide potential insights on safety and liability of AVs.
Design/methodology/approach
The actual crash data were obtained from California DMV and Sohu websites involved in collisions of AVs from 2015 to 2021 with 210 observations. The Bayesian random parameter ordered probit model was proposed to reflect the safety and liability of AVs, respectively, as well as accommodating the heterogeneity issue simultaneously.
Findings
The findings show that day, location and crash type were significant factors of injury severity while location and crash reason were significant influencing the liability.
Originality/value
The results provide meaningful countermeasures to support the policymakers or practitioners making strategies or regulations about AV safety and liability.
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Eric Yaw Naminse, Jincai Zhuang and Fangyang Zhu
There is a recent growing interest to find a lasting intervention to rural poverty (RP) in developing countries based on farmer entrepreneurship and innovation. The purpose of…
Abstract
Purpose
There is a recent growing interest to find a lasting intervention to rural poverty (RP) in developing countries based on farmer entrepreneurship and innovation. The purpose of this paper, therefore, is to examine the relation between entrepreneurship and RP alleviation in two resource-constrained provinces of China. This paper assesses the influence of three capabilities of farm entrepreneurs – educational, economic and socio-cultural – on farmer entrepreneurship growth and how these, in turn, impact alleviation of RP.
Design/methodology/approach
Household survey data comprising 363 respondents were taken from four deprived communities in two provinces of China. The paper employed structural equation modeling (SEM), using AMOS 21.0 alongside SPSS 20.0 to test the relations between the constructs.
Findings
The results show that a statistically significant and positive relation exists between entrepreneurship and RP alleviation in China. The findings of the study further reveal that qualitative growth of entrepreneurship has a stronger positive influence on RP alleviation than on quantitative growth, and socio-cultural capabilities of respondents significantly and positively affect entrepreneurial growth of farmers, rather than education and economic capabilities.
Research limitations/implications
The use of data from four communities in two provinces tends to limit the ability to generalize the findings of the study. Furthermore, the survey did not collect information on non-farm entrepreneurs, making it impossible to compare the findings from farm entrepreneurs with non-farm entrepreneurs.
Practical implications
The findings have practical implications for policy makers in rural China toward addressing targeted RP. This paper, therefore, suggests that entrepreneurship should be pursued vigorously among farmers in rural areas of China to help solve poverty. The paper also presents a useful lesson for various stakeholders in poverty alleviation programs in other developing countries.
Originality/value
This paper contributes to the academic literature on the entrepreneurship–RP alleviation nexus by combining the theory of capability and SEM in the analysis of an emerging economy such as China.
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This study aims to explore which of four chosen factors (i.e. privacy concerns, FoMO, self-disclosure and time cost) induce a feeling of strain among Facebook users in terms of…
Abstract
Purpose
This study aims to explore which of four chosen factors (i.e. privacy concerns, FoMO, self-disclosure and time cost) induce a feeling of strain among Facebook users in terms of social media fatigue (SMF), and if this occurs, whether it further influences such outcomes as discontinuance of usage (DoU) and interaction engagement decrement (IED).
Design/methodology/approach
Through an online structured questionnaire, empirical data were gathered to verify the research model, based on the stressor-strain-outcome (SSO) framework. The SEM technique was employed for assessing the hypothesized relationships.
Findings
The findings show that privacy concerns and time cost are strong antecedents of SMF and contribute significantly to its occurrence; while FoMO and self-disclosure do not exhibit any significant influence. Moreover, SMF positively and significantly affects DoU and IED.
Practical implications
This study enhances the existing body of knowledge on SMF and it can help: (1) individuals to be aware of risks and adjust their activities in balance with their well-being, and (2) social media (SM) managers to develop unique strategies to address the specific needs of SM users.
Originality/value
This research contributes to the limited literature on SMF by (1) introducing the concept of IED – as a consequence of SMF, and (2) creating measurement scales for IED.
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Xuejun Zhao, Yong Qin, Hailing Fu, Limin Jia and Xinning Zhang
Fault diagnosis methods based on blind source separation (BSS) for rolling element bearings are necessary tools to prevent any unexpected accidents. In the field application, the…
Abstract
Purpose
Fault diagnosis methods based on blind source separation (BSS) for rolling element bearings are necessary tools to prevent any unexpected accidents. In the field application, the actual signal acquisition is usually hindered by certain restrictions, such as the limited number of signal channels. The purpose of this study is to fulfill the weakness of the existed BSS method.
Design/methodology/approach
To deal with this problem, this paper proposes a blind source extraction (BSE) method for bearing fault diagnosis based on empirical mode decomposition (EMD) and temporal correlation. First, a single-channel undetermined BSS problem is transformed into a determined BSS problem using the EMD algorithm. Then, the desired fault signal is extracted from selected intrinsic mode functions with a multi-shift correlation method.
Findings
Experimental results prove the extracted fault signal can be easily identified through the envelope spectrum. The application of the proposed method is validated using simulated signals and rolling element bearing signals of the train axle.
Originality/value
This paper proposes an underdetermined BSE method based on the EMD and the temporal correlation method for rolling element bearings. A simulated signal and two bearing fault signal from the train rolling element bearings show that the proposed method can well extract the bearing fault signal. Note that the proposed method can extract the periodic fault signal for bearing fault diagnosis. Thus, it should be helpful in the diagnosis of other rotating machinery, such as gears or blades.
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The purpose of this study is to compare the thermal performance of two flow configurations in corrugated plate heat exchanger (CPHE): vertical flow configuration (CPHEvert.) and…
Abstract
Purpose
The purpose of this study is to compare the thermal performance of two flow configurations in corrugated plate heat exchanger (CPHE): vertical flow configuration (CPHEvert.) and diagonal flow configuration (CPHEdiag.). The study aims to determine the differences between these configurations and evaluate their respective thermal performance based on metrics such as heat transfer rates, pressure drop values and flow distribution.
Design/methodology/approach
The study compares the thermal performance of two flow arrangements of CPHE using identical geometrical dimensions and test conditions. Computational fluid dynamics (CFD) is employed, and a validated numerical model is used for the investigation. The comparison is based on analyzing the rate of heat transfer and pressure drop data between the two flow arrangements.
Findings
The findings indicate that the diagonal flow configuration in CPHEs offers improved flow distribution, enhanced heat transfer performance and lower pressure drop compared to the vertical flow configuration. However, the differences in general in the thermal performance of CPHEvert. and CPHEdiag. are found to be minimal.
Originality/value
To the best of the author’s knowledge, this study represents the first attempt to investigate the impact of vertical and diagonal flow configurations on the thermal performance of the CPHE.
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Xue Xin, Yuepeng Jiao, Yunfeng Zhang, Ming Liang and Zhanyong Yao
This study aims to ensure reliable analysis of dynamic responses in asphalt pavement structures. It investigates noise reduction and data mining techniques for pavement dynamic…
Abstract
Purpose
This study aims to ensure reliable analysis of dynamic responses in asphalt pavement structures. It investigates noise reduction and data mining techniques for pavement dynamic response signals.
Design/methodology/approach
The paper conducts time-frequency analysis on signals of pavement dynamic response initially. It also uses two common noise reduction methods, namely, low-pass filtering and wavelet decomposition reconstruction, to evaluate their effectiveness in reducing noise in these signals. Furthermore, as these signals are generated in response to vehicle loading, they contain a substantial amount of data and are prone to environmental interference, potentially resulting in outliers. Hence, it becomes crucial to extract dynamic strain response features (e.g. peaks and peak intervals) in real-time and efficiently.
Findings
The study introduces an improved density-based spatial clustering of applications with Noise (DBSCAN) algorithm for identifying outliers in denoised data. The results demonstrate that low-pass filtering is highly effective in reducing noise in pavement dynamic response signals within specified frequency ranges. The improved DBSCAN algorithm effectively identifies outliers in these signals through testing. Furthermore, the peak detection process, using the enhanced findpeaks function, consistently achieves excellent performance in identifying peak values, even when complex multi-axle heavy-duty truck strain signals are present.
Originality/value
The authors identified a suitable frequency domain range for low-pass filtering in asphalt road dynamic response signals, revealing minimal amplitude loss and effective strain information reflection between road layers. Furthermore, the authors introduced the DBSCAN-based anomaly data detection method and enhancements to the Matlab findpeaks function, enabling the detection of anomalies in road sensor data and automated peak identification.
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This study aims to examine the impact of Covid19 on service ecosystem self-adjustment (SES_SA) and additionally to explore the mediating role of SES_SA on the relationship between…
Abstract
Purpose
This study aims to examine the impact of Covid19 on service ecosystem self-adjustment (SES_SA) and additionally to explore the mediating role of SES_SA on the relationship between the Covid19 pandemic and the development of digital service capability (DD_SC).
Design/methodology/approach
Data were drawn from 384 business people with the help of a survey questionnaire. The interrelation of the model was examined with the help of structural equation modeling (SEM) using bootstrapping measures in Smart-partial least square (PLS). Three constructs (Covid19, DD_SC and SES_SA) were found with the help of exploratory factor analysis (EFA). Convergent and discriminant validity were obtained through confirmatory factor analysis (CFA) using statistical package for the social sciences-analysis of a moment structures (SPSS-AMOS)-V.23.
Findings
There is a substantial impact of Covid19 on SES_SA and DD_SC. The investigation also discovered that SES_SA significantly impact DD_SC, whereas, Covid19 impact DD_SC indirectly through SES_SA. Age has a significant favorable influence on fear of Covid19.
Research limitations/implications
There is scant literature linking SES_SA and the DD_SC.
Practical implications
The study promotes understanding of the contribution of Covid19 and SES_SA in the DD_SC among business people to enhance value co-creation. Capitalizing on DD_SC will enhance customer experience, assist customers in decision-making, and foster digital economic growth.
Originality/value
It enlightens on the digital capabilities needed for creating and co-creating value. Most studies in this area are qualitative/conceptually based and have not studied this kind of interrelation. Hence, it’s the only quantitative study that has examined the inter-relations among Covid19, SES_SA and DD_SC using SEM. This study also offers comprehension of all theories used in this context by relating Covid19 effects to DD_SC.
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Zhao-Peng Li, Li Yang, Si-Rui Li and Xiaoling Yuan
China’s national carbon market will be officially launched in 2020, when it will become the world’s largest carbon market. However, China’s carbon market is faced with various…
Abstract
Purpose
China’s national carbon market will be officially launched in 2020, when it will become the world’s largest carbon market. However, China’s carbon market is faced with various major challenges. One of the most important challenges is its impact on the social and economic development of arid and semi-arid regions. By simulating the carbon price trends under different economic development and energy consumption levels, this study aims to help the government can plan ahead to formulate various countermeasures to promote the integration of arid and semi-arid regions into the national carbon market.
Design/methodology/approach
To achieve this goal, this paper builds a back propagation neural network model, takes the third phase of the European Union Emissions Trading System (EU ETS) as the research object and uses the mean impact value method to screen out the important driving variables of European Union Allowance (EUA) price, including economic development (Stoxx600, Stoxx50, FTSE, CAC40 and DAX), black energy (coal and Brent), clean energy (gas, PV Crystalox Solar and Nordex) and carbon price alternatives Certification Emission Reduction (CER). Finally, this paper sets up six scenarios by combining the above variables to simulate the impact of different economic development and energy consumption levels on carbon price trends.
Findings
Under the control of the unchanged CER price level, economic development, black energy and clean energy development will all have a certain impact on the EUA price trends. When economic development, black energy consumption and clean energy development are on the rise, the EUA price level will increase. When the three types of variables show a downward trend, except for the sluggish development of clean energy, which will cause the EUA price to rise sharply, the EUA price trend will also decline accordingly in the remaining scenarios.
Originality/value
On the one hand, this paper incorporates driving factors of carbon price into the construction of carbon price prediction system, which not only has higher prediction accuracy but also can simulate the long-term price trend. On the other hand, this paper uses scenario simulation to show the size, direction and duration of the impact of economic development, black energy consumption and clean energy development on carbon prices in a more intuitive way.