Noel Scott, Brent Moyle, Ana Cláudia Campos, Liubov Skavronskaya and Biqiang Liu
Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior…
Abstract
Smart card-based E-payment systems are receiving increasing attention as the number of implementations is witnessed on the rise globally. Understanding of user adoption behavior of E-payment systems that employ smart card technology becomes a research area that is of particular value and interest to both IS researchers and professionals. However, research interest focuses mostly on why a smart card-based E-payment system results in a failure or how the system could have grown into a success. This signals the fact that researchers have not had much opportunity to critically review a smart card-based E-payment system that has gained wide support and overcome the hurdle of critical mass adoption. The Octopus in Hong Kong has provided a rare opportunity for investigating smart card-based E-payment system because of its unprecedented success. This research seeks to thoroughly analyze the Octopus from technology adoption behavior perspectives.
Cultural impacts on adoption behavior are one of the key areas that this research posits to investigate. Since the present research is conducted in Hong Kong where a majority of population is Chinese ethnicity and yet is westernized in a number of aspects, assuming that users in Hong Kong are characterized by eastern or western culture is less useful. Explicit cultural characteristics at individual level are tapped into here instead of applying generalization of cultural beliefs to users to more accurately reflect cultural bias. In this vein, the technology acceptance model (TAM) is adapted, extended, and tested for its applicability cross-culturally in Hong Kong on the Octopus. Four cultural dimensions developed by Hofstede are included in this study, namely uncertainty avoidance, masculinity, individualism, and Confucian Dynamism (long-term orientation), to explore their influence on usage behavior through the mediation of perceived usefulness.
TAM is also integrated with the innovation diffusion theory (IDT) to borrow two constructs in relation to innovative characteristics, namely relative advantage and compatibility, in order to enhance the explanatory power of the proposed research model. Besides, the normative accountability of the research model is strengthened by embracing two social influences, namely subjective norm and image. As the last antecedent to perceived usefulness, prior experience serves to bring in the time variation factor to allow level of prior experience to exert both direct and moderating effects on perceived usefulness.
The resulting research model is analyzed by partial least squares (PLS)-based Structural Equation Modeling (SEM) approach. The research findings reveal that all cultural dimensions demonstrate direct effect on perceived usefulness though the influence of uncertainty avoidance is found marginally significant. Other constructs on innovative characteristics and social influences are validated to be significant as hypothesized. Prior experience does indeed significantly moderate the two influences that perceived usefulness receives from relative advantage and compatibility, respectively. The research model has demonstrated convincing explanatory power and so may be employed for further studies in other contexts. In particular, cultural effects play a key role in contributing to the uniqueness of the model, enabling it to be an effective tool to help critically understand increasingly internationalized IS system development and implementation efforts. This research also suggests several practical implications in view of the findings that could better inform managerial decisions for designing, implementing, or promoting smart card-based E-payment system.
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Willy John Nakamura Goto, Douglas Wildgrube Bertol and Nardênio Almeida Martins
This paper aims to propose a robust kinematic controller based on sliding mode theory designed to solve the trajectory tracking problem and also the formation control using the…
Abstract
Purpose
This paper aims to propose a robust kinematic controller based on sliding mode theory designed to solve the trajectory tracking problem and also the formation control using the leader–follower strategy for nonholonomic differential-drive wheeled mobile robots with a PD dynamic controller.
Design/methodology/approach
To deal with classical sliding mode control shortcomings, such as the chattering and the requirement of a priori knowledge of the limits of the effects of disturbances, an immune regulation mechanism-inspired approach is proposed to adjust the control effort magnitude adaptively. A simple fuzzy boundary layer method and an adaptation law for the immune portion gain online adjustment are also considered. An obstacle avoidance reactive strategy is proposed for the leader robot, given the importance of the leader in the formation control structure.
Findings
To verify the adaptability of the controller, obstacles are distributed along the reference trajectory, and the simulation and experimental results show the effectiveness of the proposed controller, which was capable of generating control signals avoiding chattering, compensating for disturbances and avoiding the obstacles.
Originality/value
The proposed design stands out for the ability to adapt in a case involving obstacle avoidance, trajectory tracking and leader–follower formation control by nonholonomic robots under the incidence of uncertainties and disturbances and also considering that the immune-based control provided chattering mitigation by adjusting the magnitude of the control effort, with adaptability improved by a simple integral-type adaptive law derived by Lyapunov stability analysis.
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J.H. Huang, J.Y. Pei, Y.Y. Qian and Y.H. Jiang
In this paper, a formula for life prediction of SMT solder joints under thermal cycling has been established on a damage model. The major failure mechanisms such as fatigue, creep…
Abstract
In this paper, a formula for life prediction of SMT solder joints under thermal cycling has been established on a damage model. The major failure mechanisms such as fatigue, creep and atmospheric oxidation have been considered in the formula. The experimental verification shows that the life formula established in this paper coincides with the experimental results.
Chengping He, Jie Ren and Hao Huang
As the search engine platform, Baidu has already developed keyword advertising as one of its main business scopes, while in-feed advertising is emerging as another intelligent…
Abstract
Purpose
As the search engine platform, Baidu has already developed keyword advertising as one of its main business scopes, while in-feed advertising is emerging as another intelligent choice for the company. Our purpose is to validate the effectiveness of keyword and retargeted in-feed advertising on offline sales and whether the effectiveness of these two advertising strategies relies on keyword attributes work.
Design/methodology/approach
We utilize data from the ad campaigns of a prominent manufacturer within the machinery and equipment (hereinafter referred to as “the company”) on Baidu. To scrutinize the research hypotheses, we have employed linear regression models. Subsequently, we address potential endogeneity issues and use various techniques to ascertain the reliability of the results.
Findings
Empirical evidence indicates that both keyword and in-feed advertising enhance offline sales. Upon examining the moderating role of keyword attributes (specificity and length), we observe that specific keywords (price and word-of-mouth (WOM)) accelerate the boosting effect of advertising on sales; similarly, the longer the keywords, the more obvious the enhanced impact of advertising on sales. Moreover, the positive influence of specific keywords (price and WOM) on advertising effectiveness is more outstanding when the keywords are longer.
Originality/value
To our knowledge, no empirical investigation has yet to analyze keyword and retargeted in-feed advertising concurrently within the search engine context. Our research is the inaugural work to reveal that they serve as mutual substitutes regarding their impact on sales. Furthermore, this paper pioneers examining the moderating effects exerted by keyword attributes (specificity and length) on the effectiveness of these two ad types. The findings presented herein offer valuable insights into the harmonious coexistence and collaboration among companies, advertisers, users and search engine platforms.
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Saba S. Colakoglu, Niclas Erhardt, Stephanie Pougnet-Rozan and Carlos Martin-Rios
Creativity and innovation have been buzzwords of managerial discourse over the last few decades as they contribute to the long-term survival and competitiveness of firms. Given…
Abstract
Creativity and innovation have been buzzwords of managerial discourse over the last few decades as they contribute to the long-term survival and competitiveness of firms. Given the non-linear, causally ambiguous, and intangible nature of all innovation-related phenomena, management scholars have been trying to uncover factors that contribute to creativity and innovation from multiple lenses ranging from organizational behavior at the micro-level to strategic management at the macro-level. Along with important and insightful developments in these research streams that evolved independently from one another, human resource management (HRM) research – especially from a strategic perspective – has only recently started to contribute to a better understanding of both creativity and innovation. The goal of this chapter is to review the contributions of strategic HRM research to an improved understanding of creativity at the individual-level and innovation at the firm-level. In organizing this review, the authors rely on the open innovation funnel as a metaphor to review research on both HRM practices and HRM systems that contribute to creativity and innovation. In the last section, the authors focus on more recent developments in HRM research that focus on ambidexterity – as a way for HRM to simultaneously facilitate exploration and exploitation. This chapter concludes with a discussion of future research directions.
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Taozhi Zhuang, Haojie Ji, Ying Wang, Hongjuan Wu and Meiling Zeng
Globally, co-production is of great significance in promoting neighborhood regeneration. However, in the Chinese context, characterized by a governance system with strong…
Abstract
Purpose
Globally, co-production is of great significance in promoting neighborhood regeneration. However, in the Chinese context, characterized by a governance system with strong government discourse power and a tradition of passive public participation, co-production has faced significant challenges. To address issues, this paper aims to deeply understand the co-production behaviors and strategy choices of local governments and residents in the co-produced neighborhood regeneration.
Design/methodology/approach
An evolutionary game approach was utilized as the research method to analyze the interest interactions between the two parties, the differences and similarities in strategy choices and the influencing factors in government and resident-initiated project types, respectively. Chongqing was selected as the case area for empirical analysis, with data derived from project materials and in-depth interviews.
Findings
This study revealed dynamic interactions between local governments and residents, significant differences between the two project types regarding co-production levels, the positive role of residents' perceived loss and the effect of marginal benefits on critical influencing factors.
Originality/value
Drawing upon co-production theory, this paper elucidates how different levels of co-production are implemented and highlights the differences between the two types of neighborhood regeneration projects within governance systems characterized by strong state discourse power and a lack of public participation tradition. It addresses current issues and provides critical references for government policymakers and urban planners to make informed decisions and promote co-produced neighborhood rehabilitation projects.
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Jiawei Liu, Zi Xiong, Yi Jiang, Yongqiang Ma, Wei Lu, Yong Huang and Qikai Cheng
Fine-tuning pre-trained language models (PLMs), e.g. SciBERT, generally require large numbers of annotated data to achieve state-of-the-art performance on a range of NLP tasks in…
Abstract
Purpose
Fine-tuning pre-trained language models (PLMs), e.g. SciBERT, generally require large numbers of annotated data to achieve state-of-the-art performance on a range of NLP tasks in the scientific domain. However, obtaining fine-tuning data for scientific NLP tasks is still challenging and expensive. In this paper, the authors propose the mix prompt tuning (MPT), which is a semi-supervised method aiming to alleviate the dependence on annotated data and improve the performance of multi-granularity academic function recognition tasks.
Design/methodology/approach
Specifically, the proposed method provides multi-perspective representations by combining manually designed prompt templates with automatically learned continuous prompt templates to help the given academic function recognition task take full advantage of knowledge in PLMs. Based on these prompt templates and the fine-tuned PLM, a large number of pseudo labels are assigned to the unlabelled examples. Finally, the authors further fine-tune the PLM using the pseudo training set. The authors evaluate the method on three academic function recognition tasks of different granularity including the citation function, the abstract sentence function and the keyword function, with data sets from the computer science domain and the biomedical domain.
Findings
Extensive experiments demonstrate the effectiveness of the method and statistically significant improvements against strong baselines. In particular, it achieves an average increase of 5% in Macro-F1 score compared with fine-tuning, and 6% in Macro-F1 score compared with other semi-supervised methods under low-resource settings.
Originality/value
In addition, MPT is a general method that can be easily applied to other low-resource scientific classification tasks.
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Yaru Huang, Yaojun Ye and Mengling Zhou
This paper aims to build an improved grey panel clustering evaluation model and evaluate the comprehensive development potential of industrial economy, society and ecological…
Abstract
Purpose
This paper aims to build an improved grey panel clustering evaluation model and evaluate the comprehensive development potential of industrial economy, society and ecological environment in the Yangtze River Economic Belt of China. The purpose of this study is to provide some theoretical basis and tool support for management departments and relevant researchers engaged in industrial sustainable development.
Design/methodology/approach
This study uses the driving force pressure state impact response analysis framework to build a comprehensive evaluation index system. Based on the center point triangle whitening weight function, it classifies the panel grey clustering of improvement time and index weight.
Findings
The results show that there are great differences in the level of industrial ecological development in different regions of the Yangtze River Economic Belt, which further illustrates the scientificity and rationality of the evaluation method proposed in this paper.
Practical implications
Due to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. The improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.
Social implications
Due to the industrial ecological development is in a constantly changing state, and the information is uncertain. Whitening weight function is introduced to represent the complete information of relevant data. The industrial ecological evaluation involves a comprehensive complex system, which belongs to the panel data analysis problem. In order to improve the effectiveness of industrial ecological evaluation, the improved grey panel clustering evaluation model is applied to grade the industrial ecological development level of the Yangtze River Economic Belt. The results have important guiding significance for the balanced development of industrial ecology in the region.
Originality/value
the new model proposed in this paper complements and improves the grey clustering analysis theory of panel data, that is, aiming at the subjective limitation of using time degree to determine time weight in panel grey clustering, a comprehensive theoretical method for determining time weight is creatively proposed. Combining the DPSIR (Driving force-Pressure-State-Influence-Response) model model with ecological development, a comprehensive evaluation model is constructed to make the evaluation results more authentic and comprehensive.