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This research focused on the self-serving motivation of voice behavior from an impression management perspective, different from the previous studies on the altruistic motivation. The purpose of this study was to construct a multilevel theoretical model that proposed how political skill operates to exercise effects on employee voice behavior in the context of organizational politics climate from an impression management perspective. We hypothesized the positive relationship between political skill and employee voice behavior, and the mediating role of impression-management motives, and then examined the cross-level effects of organizational politics climate on the individual-level employee voice phenomenon. An evaluation of research limitations, suggestions for future research, contributions to the literature and practical implications were discussed finally.

Contributor(s): Professor Christopher Coker, Dr Debin Ma, Dr Yu Jie | Welcome to LSE IQ, the award-winning podcast where we ask social scientists and other experts to answer one intelligent question. In this episode Sue Windebank asks, "Is the 21st Century the Chinese century?"
This month sees the 70th anniversary of the People's Republic of China. In 1949 the Chinese Communist Party won the Chinese Civil War. Having overthrown the nationalist government of the Republic of China, Mao Zedong declared the People's Republic on October 1st in Tiananmen Square. The last 70 years have been tumultuous for the People's Republic of China. Under Mao it experienced economic break down and societal chaos. Famously the Great Leap Forward, a campaign designed to industrialise and modernise the economy, led to the largest famine in history, with millions of people dying of starvation. And yet today, after widespread market-economy reforms started by Deng Xiaoping in the 1970s, China is the second largest economy in the world. This wealth is reflected in the country's international influence, which is growing through sizeable investments the country is making in large infrastructure projects around the world. And, of course, hundreds of thousands of Chinese students study abroad every year – including at LSE. This episode features: Professor Christopher Coker, LSE Department of International Relations and LSE IDEAS; Dr Debin Ma, LSE Department of Economic History; and Dr Yu Jie, Chatham House. For further information about the podcast and all the related links visit lse.ac.uk/iq and please tell us what you think using the hashtag #LSE.

Emerging as a comprehensive and aggressive governance scheme in China, the "Social Credit System" (SCS) seeks to promote the norms of "trust" in the Chinese society by rewarding behavior that is considered "trust-keeping" and punishing those considered "trust-breaking." This Article closely examines the evolving SCS regime and corrects myths and misunderstandings popularized in the international media. We identify four key mechanisms of the SCS, i.e., information gathering, information sharing, labeling, and joint sanctions, and highlight their unique characteristics as well as normative implications. In our view, the new governance mode underlying the SCS—what we call the "rule of trust"—relies on the fuzzy notion of "trust" and wide-ranging arbitrary and disproportionate punishments. It derogates from the notion of "governing the country in accordance with the law" enshrined in China's Constitution. This Article contributes to legal scholarship by offering a distinctive critique of the perils of China's SCS in terms of the party-state's tightening social control and human rights violations. Further, we critically assess how the Chinese government uses information and communication technologies to facilitate data-gathering and data-sharing in the SCS with few meaningful legal constraints. The unbounded and uncertain notion of "trust" and the unrestrained employment of technology are a dangerous combination in the context of governance. We conclude with a caution that with considerable sophistication, the Chinese government is preparing a much more sweeping version of SCS reinforced by artificial intelligence tools such as facial-recognition and predictive policing. Those developments will further empower the government to enhance surveillance and perpetuate authoritarianism.

PurposeGamification is a strategic approach employed by practitioners to foster meaningful engagement and enhance the acceptance of recommendations. Gamification affordances (e.g. achievement, self-expression, interaction, and cooperation) catalyze significant psychological processes in consumers, leading to behavioral changes. Despite its application, a gap remains in understanding how these gamification affordances in e-commerce contexts impact customers' perceived values and drive recommendation acceptances.Design/methodology/approachEmploying affordance theory and perceived value theory as our foundation, we have crafted a comprehensive framework that addresses the multifaceted nature of e-commerce gamification, thereby unifying the fragmented knowledge in this area. We implemented a quantitative research design to empirically test the proposed model.FindingsThe research reveals that the four principal affordances of gamification – achievement, self-expression, interaction, and cooperation – significantly enrich consumer values across hedonic, utilitarian, and social dimensions. This enrichment facilitates an increased propensity for accepting recommendations.Originality/valueThis study provides a novel lens through which to view the influence of gamification affordances on recommendation acceptance within gamified e-commerce settings. It delineates the effects of each affordance on consumers' perceived value and highlights the pivotal affordances that shape gamified e-commerce experiences. These insights yield actionable strategies for practitioners aiming to refine e-commerce gamification designs and cultivate more engaging consumer interactions.

Introduction/purpose: Cutting is a typical material process. However, an appropriate solution for simultaneous optimization of material machinability and tool life in material cutting processes has not been obtained yet. In this article, probabilistic multi-objective robust design (PMORD) is expounded and the robust design problem in the simultaneous optimization of material machinability and tool life is analyzed by taking the machining of ferrite-bainite dual-phase steel as an example. Methods: According to PMORD, the arithmetic mean and its deviation of various performance and utility indexes of alternative schemes are evaluated as twin independent responses, which respectively contribute a part of the partial preferable probability to the performance indexes. In the evaluation, the arithmetic average of the utility index is taken as the representative of the utility attribute, and the evaluation is made in accordance with the function or preference of the utility index. However, the deviation term is generally used as an unbeneficial type of the index (that is, the smaller the better) to participate in the evaluation. The product of the two parts of partial preferable probability is the actual partial preferable probability of the corresponding performance index. The product of the partial preferable probability of all performance utility indexes gives the total preferable probability of the corresponding scheme, which is the only index for each scheme to participate in the competition in robust design. Results: The optimization result of this example is that the tool life is 1297.3333 s (standard deviation is 2.0817 s) and the surface roughness is 2.22mm (standard deviation is 0.2mm), while the corresponding working conditions are that the heat treatment temperature of the material is 790°C, the cutting speed is 150m/min, the feed speed is 0.15mm/rev, and the cutting depth is 0.2mm. Conclusion: The example of the parameter optimization of cutting of ferrite-bainite dual-phase steel by means of PMORD indicates the rationality of the appropriate solution.

Introduction/purpose: Turning is a typical machining process. However, an appropriate solution for a concurrent optimization of minimizing surface roughness, minimizing cutting forces and vibrations, and maximizing the material removal rate in turning processes has not been found yet. This article formulates the rule of separating an independent attribute from multiple attributes by using the linear correlation coefficient in the spirit of the cluster analysis first. Moreover, the evaluation of the concurrent optimization of steel turning by means of probability - based multi - objective optimization (PMOO) is taken as an example to show the procedure including the separation of an independent attribute from multiple attributes by using PMOO. Methods: PMOO is a promising solution for turning processes. It is necessary to have an independent attribute in the evaluation of PMOO to be analogical as an independent event in the view of the probability theory. The separation of an independent attribute from multiple attributes by using the linear correlation coefficient is conducted in the spirit of the cluster analysis. It further assumes that if the linear correlation coefficient of two attributes in the cluster analysis is higher than 0.8, i.e., in case of very strong correlation, then they could be put into one category, and only one of them could be taken as an independent attribute to join the evaluation of PMOO. Results: The formulation reflects the essence of PMOO and its application in material machining rationally, which opens a new way for solving the relevant problem. The example of the parameter optimization of steel turning by means of PMOO indicates the rationality of the appropriate solution. Conclusion: This innovative study has practical significance of making the utilization of PMOO method reasonable by providing a rational rule of separating independent attributes from multiple attributes of PMOO.

Introduction/purpose: In this paper, a new approach to solving the portfolio investment problem is formulated to handle simultaneous optimization of both maximizing the rate of return and minimizing the variance of the rate of return. Probability - based multi - objective optimization is combined with uniform design for experiments with mixtures to conduct processing. Methods: Preliminarily, probability - based multi - objective optimization is employed to synthesize the bi-objective problem of simultaneous optimization of both maximizing the rate of return and minimizing the variance of the rate of return into a single objective one of the total preferable probability of each alternative scenario. The total preferable probability is the product of all partial preferable probabilities of each performance utility; subsequently, the method of uniform design for experiments with mixtures is used to create a set of effective sampling points for the portfolio investment problem to provide discretization in data processing and simplifying treatment, of which the proportion xi follows the constraint condition of xl + x2 + x3...+ xs = 1 with the total number of variables s for xi. Results: The new approach is used to deal with the portfolio Investment problem that is, in essence, simultaneous optimization of both maximizing the rate of return and minimizing the variance of the rate of return, which leads to reasonable consequences. The results are with the quality of rationality from the respect of the probability theory for simultaneous optimization of multiple objectives. Conclusion: This method naturally reflects the essence of the portfolio investment problem and opens a new way of solving the relevant problem.