Search results

This study adopts self-determination theory and stimulus-organism-response framework to develop a model that explores the motivations of such donors by considering their self-determination needs and extrinsic and intrinsic motivations.

Based on online survey data collected from 436 crowdfunding donors in China, this study follows a structural equation modeling analysis to test hypotheses.

The results indicate that perceived ease of use, perceived self-efficacy and social connection have positive effects on the donation intentions of backers through a combination of extrinsic and intrinsic motivations.

The findings shed light on various extrinsic and intrinsic motivations advancing knowledge of individual fund motivation in donation-based crowdfunding and provide guidelines for the development of donation-based crowdfunding theory and practice.

Academic and practitioner attention to the constructs of authentic leadership and work engagement and their implications for organizations has grown dramatically over the past decade. Consideration of the implications of these constructs for high-performance human resource practices (HPHRP) is limited, however. In this monograph, we present a conceptual model that integrates authentic leadership/followership theory with theory and research on HPHRP. Then, we apply this model to systematically consider the implications of skill-enhancing, motivation-enhancing, and opportunity-enhancing HR practices in combination with authentic leadership for authentic followership, follower work engagement, and follower performance. We contend that authentic leadership, through various influences processes, promotes HPHRP, and vice versa, to help foster enhanced work engagement. By cultivating greater work engagement, individuals are motivated to bring their best, most authentic selves to the workplace and are more likely to achieve higher levels of both well-being and performance.

This study proposes a novel method utilising a speech-word pair bipartite network to examine the correlation structure between members of parliament (MPs) in the context of the UK- China relationship.

We construct MP-word pair bipartite networks based on the co-occurrence relationship between MPs and words in their speech content. These networks are then mapped into monopartite MPs correlation networks. Additionally, the study calculates correlation network indicators and identifies MP communities and factions to determine the characteristics of MPs and their interrelation in the UK-China relationship. This includes insights into the distribution of key MPs, their correlation structure and the evolution and development trends of MP factions.

Analysis of the parliamentary speeches on China-related affairs in the British Parliament from 2011 to 2020 reveals that the distribution and interrelationship of MPs engaged in UK-China affairs are centralised and discrete, with a few core MPs playing an integral role in the UK-China relationship. Among them, MPs such as Lord Ahmad of Wimbledon, David Cameron, Lord Hunt of Chesterton and Lord Howell of Guildford formed factions with significant differences; however, the continuity of their evolution exhibits unstableness. The core MP factions, such as those led by Lord Ahmad of Wimbledon and David Cameron, have achieved a level of maturity and exert significant influence.

The research has several limitations that warrant acknowledgement. First, we mapped the MP-word pair bipartite network into the MP correlation network for analysis without directly analysing the structure of MPs based on the bipartite network. In future studies, we aim to explore various types of analysis based on the proposed bipartite networks to provide more comprehensive and accurate references for studying UK-China relations. In addition, we seek to incorporate semantic-level analyses, such as sentiment analysis of MPs, into the MP-word -pair bipartite networks for in-depth analysis. Second, the interpretations of MP structures in the UK-China relationship in this study are limited. Consequently, expertise in UK-China relations should be incorporated to enhance the study and provide more practical recommendations.

Firstly, the findings can contribute to an objective understanding of the characteristics and connotations of UK-China relations, thereby informing adjustments of focus accordingly. The identification of the main factions in the UK-China relationship emphasises the imperative for governments to pay greater attention to these MPs’ speeches and social relationships. Secondly, examining the evolution and development of MP factions aids in identifying a country’s diplomatic focus during different periods. This can assist governments in responding promptly to relevant issues and contribute to the formulation of effective foreign policies.

First, this study expands the research methodology of parliamentary debates analysis in previous studies. To the best of our knowledge, we are the first to study the UK-China relationship through the MP-word-pair bipartite network. This outcome inspires future researchers to apply various knowledge networks in the LIS field to elucidate deeper characteristics and connotations of UK-China relations. Second, this study provides a novel perspective for UK-China relationship analysis, which deepens the research object from keywords to MPs. This finding may offer important implications for researchers to further study the role of MPs in the UK-China relationship.

This study proposes a novel scheme for analysing the correlation structure between MPs based on bipartite networks. This approach offers insights into the development and evolving dynamics of MPs.

This paper points out new directions for the deepening and broadening of the institution-based view, by drawing on three streams of research with which I have been involved recently: (1) outward foreign direct investment from emerging economies, (2) bankruptcy laws and entrepreneurship development, and (3) institution-based research focusing on Africa. Such deepening has been accomplished by enhancing our institution-based understanding of foreign direct investment with a focus on emerging multinationals, while broadening has been done both substantively by probing into the impact of bankruptcy laws on entrepreneurship development around the world and geographically by calling for enhanced research attention on Africa via an institution-based lens.

Placement prominence is a multidimensional concept. Previous studies have defined and operationalized prominence in different ways, and no studies have tried to systematically examine what should and should not be counted as prominence. This study aims to fill this gap.

Using a content analysis of six short films and a survey study on 129 Chinese young adults, this study systematically examined 13 dimensions of placement prominence on the memory of placed brands.

Factor analysis has reduced the 13 dimensions into five factors: contextual, narrative, sensory, exposure and spatial prominence. Fuzzy-set qualitative comparative analysis (QCA) software was used to conduct a contrarian case analysis and test for predictive validity. This was followed by a QCA to identify the optimal configurations of the five factors that may lead to a high recognition of the placed brands. The optimal configurations were also contrasted across two gender and brand familiarity groups. While the optimal configurations of prominence on brand memory for male and female participants were largely the same, the combinations differed between participants with low and high brand familiarity.

Previous studies in product placement usually operationalize prominence with a few dominant dimensions intuitively though several other dimensions, and their interactions could also affect the prominence level. To the best of authors’ knowledge, this is the first study that used multiple dimensions of prominence configurations to identify paths that may lead to low and high brand memory. The empirical results contribute to the theory and understanding of the effect of prominence on brand memory and provide guidance to brand managers in determining which prominence configuration is the most suitable for achieving their promotional objective.

This paper aims to establish the predictive equations of height, area and volume of printed solder paste during solder paste stencil printing (SPSP) process in surface mount technology (SMT) to better understand the effect of process parameters on the printing quality.

An experiment plan is proposed based on the response surface method (RSM). Experiments with 30 different combinations of process parameters are performed using a solder paste printer. After printing, the volume, area and height of the printed SAC105 solder paste are measured by a solder paste inspection machine. Using RSM, the predictive equations associated with the printing parameters and the printing quality of the solder paste are formed.

The optimal printing parameters are 175.08 N printing pressure, 250 mm/s printing speed, 0.1 mm snap-off height and 15.7 mm/s stencil snap-off speed if the target height of solder paste is 100 µm. As the target printing area of solder paste is 1.1 mm × 1.3 mm, the optimized values of the printing parameters are 140.29 N, 100.52 mm/s, 0.63 mm and 20.25 mm/s. When both the target printing height and area are optimized together, the optimal values for the four parameters are 86.67 N, 225.76 mm/s, 0.15 mm and 1.82 mm/s.

A simple RSM-based experimental method is proposed to formulate the predictive polynomial equations for height, area and volume of printed solder paste in terms of important SPSP parameters. The predictive equation model can be applied to the actual SPSP process, allowing engineers to quickly predict the best printing parameters during parameter setting to improve production efficiency and quality.

The main purpose of this study is to empirically investigate the impact of intellectual capital efficiency on US multinational software companies' performance from 2012 to 2016 by applying data envelopment analysis (DEA).

It adopts a new slacks-based measure (SBM) to obtain a more accurate performance estimation and rank between companies. Regression analysis is used to test the overall IC and each of its elements (Human Capital, Innovation Capital, Process Capital and Customer Capital).

The univariate result shows that multinational companies are more efficient than non-multinational companies. However, the regression result shows that multinationality can hardly explain the firm efficiency of software firms. Another interesting finding is that intellectual capital has a positive and significant impact on software firm performance in the US human capital influences firm efficiency directly. However, when human capital is combined with the other elements of IC, the contribution of human capital becomes less significant. This is because people may think that innovation capital, process capital and customer capital can replace human capital, but it is not. In short, human capital may affect firm efficiency through other elements of IC (innovation capital, process capital and customer capital) as it is the base of other elements.

The results show that multinational companies have higher efficiency scores than non-multinational companies. In addition, Intellectual capital has a positive and significant impact on software firm performance in the US human capital influences firm efficiency directly. However, when human capital is combined with the other elements of IC, the contribution of human capital becomes less significant. This is because people may think that innovation capital, process capital and customer capital can replace human capital, but it is not. In short, human capital may affect firm efficiency through other elements of IC (innovation capital, process capital and customer capital) as it is the base of other elements.

Overall, the study highlights the needs of having intellectual capital and its elements (Human Capital, Innovation Capital, Process Capital and Customer Capital) to increase firm efficiency.

First, the authors use a more comprehensive elements of IC, which are human capital, innovation capital, process capital and customer capital for a better IC measurement. Second, this study makes the first attempt using the DSBM model via DEA to examine the operating efficiency of US multinational software firms.

This chapter provides a survey of alternative methodologies for measuring and comparing productivity and efficiency of airlines, and reviews representative empirical studies. The survey shows the apparent shift from index procedures and traditional OLS estimation of production and cost functions to stochastic frontier methods and Data Envelopment Analysis (DEA) methods over the past three decades. Most of the airline productivity and efficiency studies over the last decade adopt some variant of DEA methods. Researchers in the 1980s and 1990s were mostly interested in the effects of deregulation and liberalization on airline productivity and efficiency as well as the effects of ownership and governance structure. Since the 2000s, however, studies tend to focus on how business models and management strategies affect the performance of airlines. Environmental efficiency now becomes an important area of airline productivity and efficiency studies, focusing on CO₂ emission as a negative or undesirable output. Despite the fact that quality of service is an important aspect of airline business, limited attempts have been made to incorporate quality of service in productivity and efficiency analysis.