Shu-sien Liao, Da-chian Hu, Yu-Chun Chung and Li-Wen Chen
The purpose of this paper is to investigate the relationship between leader-member exchange (LMX), job satisfaction (JS), life satisfaction (LS), and psychological capital (PC…
Abstract
Purpose
The purpose of this paper is to investigate the relationship between leader-member exchange (LMX), job satisfaction (JS), life satisfaction (LS), and psychological capital (PC) for employee relation management.
Design/methodology/approach
A total of 319 valid questionnaires were received from employees of financial and electronics manufacturing industries in Taiwan, and they were then analyzed using a structuring equation model with SPSS 12.0 and LISREL 8.8.
Findings
Good LMX increases psychological capital. Psychological capital enhances both JS and LS, and psychological capital serves as a full mediator for both JS and LS. A moderating effect of industrial characteristics is found between LMX and LS and between psychological capital and LS.
Practical implications
The findings suggest that managers need to focus on leadership style in order to develop employees’ life and JS through building psychological capital.
Originality/value
This study not only obtained further support for predictions derived from the LMX theory but was also a more extensive analysis of the meaningful relationships between job and LS with a mediating effect of psychological capital on employee relation management.
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Wen Li, Zhongbin Bao, Lijun Chen and Dongshun Deng
At present, the conventional method of preparing cationic fluorinated acrylic latex is to emulsify copolymerised monomers with cationic surfactants. However, there has been a wide…
Abstract
Purpose
At present, the conventional method of preparing cationic fluorinated acrylic latex is to emulsify copolymerised monomers with cationic surfactants. However, there has been a wide concern about using Gemini surfactants to prepare cationic polymer latex to improve its properties. The purpose of this paper was to focus on the synthesis of novel self-crosslinked cationic fluorinated acrylic latex (SCFAL), during which the copolymerised monomers were initiated with a water soluble azo initiator and emulsified with mixed surfactants of Gemini emulsifier and alkyl polyglycoside (APG).
Design/methodology/approach
The novel SCFAL was prepared successfully by the semi-continuous seeded emulsion polymerisation of butyl acrylate, methyl methacrylate, hexafluorobutyl methacrylate (HFMA) and hydroxy propyl methacrylate (HPMA) in aqueous medium.
Findings
The conversion is the maximum and the coagulation percentage the minimum when the amounts of emulsifier and initiator are 8 and 0.6 per cent, respectively. The average particle size of the latex is significantly reduced with the increase of the amount of emulsifiers used. However, the average particle size of the latex is increased with the increase of the amount of HPMA. The particle size of the latex is of a unimodal distribution, which means that the particle size was reasonably uniform. Contact angle is increased with the increase of the amount of the HFMA.
Practical implications
The novel SCFAL can be widely used as significant components in the field of coatings, leather, textile, paper, adhesives and so on.
Originality/value
SCFAL, which was emulsified with novel mixed surfactants of Gemini surfactant and APG, has been prepared successfully. Influences of amount of initiator, emulsifier, HPMA and HFMA on emulsion polymerisation and/or properties of novel latex are investigated in detail.
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Che-Jung Chang, Chien-Chih Chen, Wen-Li Dai and Guiping Li
The purpose of this paper is to develop a small data set forecasting method to improve the effectiveness when making managerial decisions.
Abstract
Purpose
The purpose of this paper is to develop a small data set forecasting method to improve the effectiveness when making managerial decisions.
Design/methodology/approach
In the grey modeling process, appropriate background values are one of the key factors in determining forecasting accuracy. In this paper, grey compensation terms are developed to make more appropriate background values to further improve the forecasting accuracy of grey models.
Findings
In the experiment, three real cases were used to validate the effectiveness of the proposed method. The experimental results show that the proposed method can improve the accuracy of grey predictions. The results further indicate that background values determined by the proposed compensation terms can improve the accuracy of grey model in the three cases.
Originality/value
Previous studies determine appropriate background values within the limitation of traditional grey modeling process, while this study makes new background values without the limitation. The experimental results would encourage researchers to develop more accuracy grey models without the limitation when determining background values.
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Siew Chen Sim, Sheng Huang, Michael James Mustafa and Wen Li Chan
This study aims to explore how training influences employee proactive behaviours in entrepreneurial ventures. Specifically, the study develops and tests a model in which…
Abstract
Purpose
This study aims to explore how training influences employee proactive behaviours in entrepreneurial ventures. Specifically, the study develops and tests a model in which organisational identification (OID) mediates the relationship between perceptions of training and two employee proactive behaviours: taking charge and creative behaviour.
Design/methodology/approach
Data was collected from 136 employee-supervisor dyads from 24 entrepreneurial ventures in Malaysia’s high technology industry. Smart–partial least square structural equations modelling was used to test our proposed hypothesis.
Findings
The findings suggest that entrepreneurial ventures can use training to strengthen employees’ identification with the ventures, which in turn encourages proactive behaviours.
Originality/value
This study shows how HRD practices found in larger firms can work in different ways to influence desirable behaviours among employees of entrepreneurial firms. Specifically, by demonstrating how the relationship between training and employee proactive behaviours occurs through OID in the context of entrepreneurial ventures, the authors provide a complementary explanation of how HRD practices in entrepreneurial ventures can influence employee positive behaviours.
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Wenxin Guo and Joseph A. Clougherty
We question whether the Chinese state has played an effective role in promoting outward foreign direct investment via its “Go Global” policies. Using the literature in…
Abstract
We question whether the Chinese state has played an effective role in promoting outward foreign direct investment via its “Go Global” policies. Using the literature in International Management as our framing, we observe three inter-related stylized realities. First, it is state-owned enterprises (SOEs) – not private enterprises – that tend to principally benefit from the favorable “Go Global” policies. Second, SOEs tend to pay much higher acquisition premiums in outward FDI as compared to non-SOEs. Third, SOEs tend to be less effective as compared to non-SOEs in gaining synergies and enhancing competitiveness as a result of these cross-border experiences. These results yield clear policy implications for the Chinese government: first, more effective public policy would involve enhanced targeting of private enterprises as the recipients of policies promoting outward FDI; second, the Chinese government should continue along the path toward privatization of SOEs. The continued bolstering of economic and social development in China is contingent upon efforts to reduce the state’s active role in outward FDI.
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Melissa Li Wen Lim, Shi Yee Wong and Chu Sheng Ding
The industrial revolution 4.0 (IR4.0) signifies technological advancements and digitalization. The fragmented and labour-intensive nature of the construction industry inherently…
Abstract
Purpose
The industrial revolution 4.0 (IR4.0) signifies technological advancements and digitalization. The fragmented and labour-intensive nature of the construction industry inherently possesses difficulties for IR4.0 adoption compared to other industries. This paper aims to investigate the perspectives of quantity surveying students on the challenges of IR4.0 implementation in the construction industry.
Design/methodology/approach
A questionnaire survey were distributed to a population of 191 quantity surveying students, with 96 valid responses returned. Descriptive statistics and factor analysis were employed to analyse the collected data.
Findings
Factor analysis revealed eight components as the key challenges for IR4.0 implementation, which revolved around resistance to change, data security issues, etc.
Practical implications
The findings could provide a guideline to higher education institutions on certain IR4.0-related areas to be incorporated into the syllabus, in ensuring that the students are equipped with such skills and knowledge, in meeting market demands. The construction stakeholders' could look into the identified challenges for strategizing the organizations in moving towards IR4.0 adoption.
Originality/value
To the best of the authors’ knowledge, this is the first study to investigate quantity surveying students' perspectives on the challenges of IR4.0 implementation in the construction industry by employing factor analysis method. The findings contribute to the body of knowledge in relation to the opinions of a younger generation who has more exposure towards technology on the hindrance of IR4.0 adoption.
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Wen Li, Bin Guo and Gangxiang Xu
Based on the linkage-leverage-learning (LLL) framework developed by Mathews (2006), the purpose of this paper is to examine how linking, leveraging and learning capabilities…
Abstract
Purpose
Based on the linkage-leverage-learning (LLL) framework developed by Mathews (2006), the purpose of this paper is to examine how linking, leveraging and learning capabilities influence the choice of foreign-entry mode, and the way such influences are contingent on context factors in the emerging markets.
Design/methodology/approach
Contrary to a prior literature applying the LLL framework, which mainly used case studies, this paper adopts a quantitative approach and is based on a sample of 321 Chinese listed companies to test the hypotheses.
Findings
The results show that multinational firms from emerging markets (EMFs) with stronger LLL capabilities are more likely to choose the wholly owned mode in foreign entries. In addition, the relationship between linking capability and wholly owned entry mode choice is weaker at higher levels of cultural distance between home and host country. At the same time, the relationship between learning capability and wholly owned entry mode choice is weaker at higher levels of cultural distance between home and host country, and of institutional distance between prior entries and the focal entry.
Research limitations/implications
An entry mode strategy for firms without ownership advantages and the identification of boundary conditions for applying different LLL capabilities are recommended. The generalizability of the findings from a single-country setting still needs further validation with other emerging economies.
Originality/value
This paper treats internationalization of firms from emerging countries with a different perspective. The underlying idea in this study is that internationalization is not only a process for EMFs to utilize externally accessible assets abroad, but also a process of simultaneously combining internationalization with experiential learning and capability utilization in overseas markets. In addition, the authors also contribute to the literature by providing strong empirical evidence for validating the LLL model and extending the existing entry mode studies.
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Meng-Hsiang Hsu, Li-Wen Chuang and Cheng-Se Hsu
The purpose of this paper is to provide a better picture of factors influencing behavioral decisions in online shopping by identifying different targets of trust and discussing…
Abstract
Purpose
The purpose of this paper is to provide a better picture of factors influencing behavioral decisions in online shopping by identifying different targets of trust and discussing their antecedents and outcomes.
Design/methodology/approach
Online survey data from 242 ihergo members were used to test the proposed model, and structural equation modeling with partial least squares was performed to analyze the measurement and structural models.
Findings
The findings show that the four types of trust identified in this study are critical determinants of perceived risk and attitude. In addition, the majority of the antecedents are found to be associated with their respective types of trust.
Research limitations/implications
The research extends the theory of reasoned action and prior research to discuss four types of consumer trust, as well as their respective antecedents and subsequent consequences. The result is a more descriptive model that better explicates consumers’ decision-making processes in online shopping.
Practical implications
Given the intense competition between online shopping sites, web site managers should strive to provide a safe and user-friendly shopping environment. In addition, the vendor can enhance trust by encouraging satisfied customers to provide positive endorsements.
Originality/value
This study is possibly the first of its kind, in identifying the four types of trust and their respective antecedents in the context of an online group-buying auction, and thus serves to enrich the existing literature concerning trust-building factors.
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Wangoo Lee, Jan Dul and Zsofia Toth
Necessary conditions represent the factors that cannot be compensated but must be present to aim the desired outcome; if a necessary condition is absent, the outcome will not…
Abstract
Necessary conditions represent the factors that cannot be compensated but must be present to aim the desired outcome; if a necessary condition is absent, the outcome will not exist. This logic of necessity causality differs from the conventional logic that has been evaluated by the methods drawing the lines “through the middle of the data” (e.g., regression and SEM). The authors argue that the empirical investigation of necessity causality has been largely ignored in hospitality and tourism literature although the notion of necessary causes for achieving certain outcomes is widespread throughout the studies. Thus, the authors introduce “necessary condition analysis” (NCA) as a suitable analytical method to identify necessary conditions in hospitality and tourism research. This chapter provides details on the underlying logic, key advantages, and an illustrative example of NCA. The chapter concludes by offering a few recommendations for future NCA applications in hospitality and tourism research.
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Wen Li, Wei Wang and Wenjun Huo
Inspired by the basic idea of gradient boosting, this study aims to design a novel multivariate regression ensemble algorithm RegBoost by using multivariate linear regression as a…
Abstract
Purpose
Inspired by the basic idea of gradient boosting, this study aims to design a novel multivariate regression ensemble algorithm RegBoost by using multivariate linear regression as a weak predictor.
Design/methodology/approach
To achieve nonlinearity after combining all linear regression predictors, the training data is divided into two branches according to the prediction results using the current weak predictor. The linear regression modeling is recursively executed in two branches. In the test phase, test data is distributed to a specific branch to continue with the next weak predictor. The final result is the sum of all weak predictors across the entire path.
Findings
Through comparison experiments, it is found that the algorithm RegBoost can achieve similar performance to the gradient boosted decision tree (GBDT). The algorithm is very effective compared to linear regression.
Originality/value
This paper attempts to design a novel regression algorithm RegBoost with reference to GBDT. To the best of the knowledge, for the first time, RegBoost uses linear regression as a weak predictor, and combine with gradient boosting to build an ensemble algorithm.