Personality and espoused cultural differences in technostress creators

This study examines the individual differences in ‘technostress creators'—defined as the factors that cause technostress for employees. Drawing on the Five-Factor model of personality and Hofstede's cultural values framework, this study proposes that the Big-Five personality traits and the espoused cultural values explain variation in technostress creators beyond the traditional antecedent measures of age, gender, education, and computer confidence. Further, in line with the insights from extant behavioral studies on “personality–culture” interaction, this study posits that the Big-Five personality traits can be linked to technostress creators more closely when each of them is accompanied by the espoused cultural value of long-term orientation than when without it. Analyzing data from an online survey of 322 full-time employees in India, results indicated that (1) the personality traits of agreeableness, neuroticism and openness to experience, and the espoused cultural values of masculinity and power distance are the key predictors of technostress creators; and (2) the relationships of agreeableness, conscientiousness and extraversion with technostress creators are contingent on espoused long-term orientation. Findings of this study contribute to the knowledge base of technostress by understanding the linkages of (and among) personality and culture with technostress creators.     

Tuning Users' Innovativeness During Ideation

Although there is increasing acknowledgement that consumers can contribute useful ideas during the development of innovative services, there has been little empirical examination of how such users can best be managed in order to contribute their ideas to the ‘fuzzy front end’ of new service development. The present study examines the relationship between the nature of user‐created ideas regarding new technology‐based services and the characteristics of the users supplying the ideas. In particular, the study investigates whether users' ideas become more incremental or more radical depending on the users' awareness of technological restrictions and their utilization of use experience. The results show that idea creators with high use experience who are unaware of any technological restrictions tend to produce service ideas that are more radical in nature, whereas idea creators with high use experience who are aware of technological restrictions tend to produce service ideas that are more incremental in nature. The study provides empirical support that, in order to provide innovative ideas, ordinary users involved in ideation must both have a contextual use experience and not be restricted in their ideation by ‘too much’ technology information and restrictions on potential feasibility.     

User idea implementation in open innovation communities: Evidence from a new product development crowdsourcing community

In collaborative crowdsourcing communities for open innovation, users generate and submit ideas as idea co‐creators. Firms then select and implement valuable ideas for new product development. Despite the popularity and success of these open innovation communities, relatively little is known about the factors that determine the implementation of the user‐generated ideas. Based on research on individual creativity, we propose a conceptual model integrating users' previous experience, idea presentation characteristics and feedback valence to explain the likelihood of idea implementation. We validate our research model with a panel data analysis of 43 550 ideas submitted by 16 360 users in the MIUI new product development community hosted by Xiaomi, a large electronics manufacturing company in China. We find an inverted U‐shaped relationship between users' past successful experience and idea implementation. Furthermore, the length of ideas is positively associated with the likelihood of idea implementation. There is also an inverted U‐shaped relationship between supporting evidence and idea implementation. Finally, we demonstrate the negative effect of positive feedback and the positive effect of negative feedback on idea implementation. These findings offer rich insights to understand the phenomenon of open innovation better. Theoretical and practical implications are discussed.     

Digital diversity among upper secondary students: A multilevel analysis of the relationship between cultural capital,self-efficacy,strategic use of information and digital competence

This paper addresses digital diversity among upper secondary students. Since 2006 digital skills and competence has been embedded as key competence in the Norwegian national curriculum. A sample of 593 Norwegian students from 43 upper secondary schools participated in a survey with a digital competence quiz and a self-report questionnaire. Analysis showed differences in students' digital competence and indication of digital diversity on both student and school level. A multilevel analysis reveals that cultural capital, language integration at home, self-efficacy, strategic use of information and average grades of the students predict 20% of the variation in students' digital competence score and 49% of the variation between schools' average digital competence score.     

Cultural algorithm-based quantum-behaved particle swarm optimization

A hybrid quantum-behaved particle swarm optimization (QPSO) based on cultural algorithm (CA), which we call cultural QPSO, is proposed. Although QPSO is a promising algorithm for many optimization problems, it is apt to lose the diversity of the swarm in the later period of the search and prematurely converges to the local optimum. Inspired by the structure of human society, this paper uses the CA model to diversify the QPSO population and improve the QPSO's performance. In this model, the swarm is divided into two sub-swarms: the common particle and the elite particle sub-swarm. If a particle comes from a common sub-swarm, it will evolve according to the QPSO method, and during the evolvement, it will be affected not only by the other common particles but also by the elites. For the elites, the differential evolution (DE) method is adopted for evolvement. After each generation, the elites will be re-elected from the whole swarm according to fitness values. The simulation results on benchmark functions demonstrate that cultural QPSO outperforms the original QPSO for many problems.     

LINGO : Visually Debiasing Natural Language Instructions to Support Task Diversity

Cross-task generalization is a significant outcome that defines mastery in natural language understanding. Humans show a remarkable aptitude for this, and can solve many different types of tasks, given definitions in the form of textual instructions and a small set of examples. Recent work with pre-trained language models mimics this learning style: users can define and exemplify a task for the model to attempt as a series of natural language prompts or instructions. While prompting approaches have led to higher cross-task generalization compared to traditional supervised learning, analyzing ‘bias’ in the task instructions given to the model is a difficult problem, and has thus been relatively unexplored. For instance, are we truly modeling a task, or are we modeling a user's instructions? To help investigate this, we develop LINGO, a novel visual analytics interface that supports an effective, task-driven workflow to (1) help identify bias in natural language task instructions, (2) alter (or create) task instructions to reduce bias, and (3) evaluate pre-trained model performance on debiased task instructions. To robustly evaluate LINGO, we conduct a user study with both novice and expert instruction creators, over a dataset of 1,616 linguistic tasks and their natural language instructions, spanning 55 different languages. For both user groups, LINGO promotes the creation of more difficult tasks for pre-trained models, that contain higher linguistic diversity and lower instruction bias. We additionally discuss how the insights learned in developing and evaluating LINGO can aid in the design of future dashboards that aim to minimize the effort involved in prompt creation across multiple domains.     

A multipopulation cultural algorithm using fuzzy clustering

In this paper, we propose a new model for multimodal function optimization, based on the concepts of cultural algorithms and fuzzy clustering. Fuzzy clustering is used in order to partition a same population into communicating subpopulations which evolve in parallel, whilst cultural exchange ensures preserving population diversity. The ability of this model to identify global/local optima without loss of diversity is demonstrated using several multimodal test functions, including a deceptive example.     

Action diversity in a simulation of the Israeli-Palestinian conflict

This article explores the strategies used by Israeli students to resolve the Israeli-Palestinian conflict in the interactive computer game, PeaceMaker. Students played PeaceMaker in the roles of both the Israeli Prime Minister and the Palestinian President in random order. Students must take actions satisfying constituents on both sides of the conflict in order to win the game. The diversity of actions taken in each role was measured. Several hypotheses test the degree to which Israeli students, depending on which role they played and their own demographic variables, exploited a consistent set of actions or explored a more diverse range of actions across three main types: construction, political, and security. The results show that (1) greater action diversity increases success in both roles, (2) Israeli students engaged in less diverse actions when playing the Israeli role than when playing the Palestinian role, (3) students’ religiosity and political Hawkishness negatively predicted action diversity when playing the Palestinian role, and (4) action diversity mediates the relationship between a student’s background knowledge about the conflict and success in the Israeli role. The significance of these findings for understanding attitudes about the Israeli-Palestinian conflict are discussed, including implications for conflict resolution more generally.     

Decentring the Creative Self: How Others Make Creativity Possible in Creative Professional Fields

Since its inception, the psychology of creativity has been concerned primarily with the study of individual creators. In contrast, this research is dedicated to an exploration of (a) who has a significant impact on a creative professional's activity and (b) what the contribution is that others make to creative outcomes. The research included interviews with 60 professionals working in science and creative industries in France. The following categories of others emerged: family and friends, peers and students, clients and funders, critics and gatekeepers, and the general public – and they were related to themes depicting the interaction between these different others and the creator. Findings reveal both similarities and differences across the five domains in terms of the specific contribution of others to the creative process. Social interactions play a key formative, regulatory, motivational and informational role in relation to creative work. From ‘internalized’ to ‘distant’, other people are an integral part of the equation of creativity calling for a de‐centring of the creative self and its re‐centring in a social space of actions and interactions.     

Behavioral diversity, choices and noise in the iterated prisoner's dilemma

Real-world dilemmas rarely involve just two choices and perfect interactions without mistakes. In the iterated prisoner's dilemma (IPD) game, intermediate choices or mistakes (noise) have been introduced to extend its realism. This paper studies the IPD game with both noise and multiple levels of cooperation (intermediate choices) in a coevolutionary environment, where players can learn and adapt their strategies through an evolutionary algorithm. The impact of noise on the evolution of cooperation is first examined. It is shown that the coevolutionary models presented in this paper are robust against low noise (when mistakes occur with low probability). That is, low levels of noise have little impact on the evolution of cooperation. On the other hand, high noise (when mistakes occur with high probability) creates misunderstandings and discourages cooperation. However, the evolution of cooperation in the IPD with more choices in a coevolutionary learning setting also depends on behavioral diversity. This paper further investigates the issue of behavioral diversity in the coevolution of strategies for the IPD with more choices and noise. The evolution of cooperation is more difficult to achieve if a coevolutionary model with low behavioral diversity is used for IPD games with higher levels of noise. The coevolutionary model with high behavioral diversity in the population is more resistant to noise. It is shown that strategy representations can have a significant impact on the evolutionary outcomes because of different behavioral diversities that they generate. The results further show the importance of behavioral diversity in coevolutionary learning.     

Casting for service innovation: The roles of frontline employees

The purpose of this paper is to explore the roles of frontline employees (FLEs) in service innovation processes and how they contribute to these roles. In the literature, FLEs are argued to play an important role in service innovation; however, neither the potential types of roles nor what taking on these potential roles means to FLEs, have previously been studied. This study investigates FLEs' actions in different types of service innovation processes. Based on analyses of eight different service business units, FLEs are identified as having either of two sets of roles: (1) leading roles as idea creators, developers and implementers, or (2) supporting roles as problem reporters, advisors and executors. The analysis provides managers with guidelines which can help them to better utilize FLEs as contributors to service innovation, either as leading or supporting actors. These imply different management challenges, which are discussed. Advice on how to tackle these challenges is given on the basis of the findings.     

Computer aided art design Ps course teaching based on FPGA and embedded system graphics processing

Photoshop Spread through electronic media, the source of presentation to development, receipt and visual coordinators. The result of accessible media innovations has empowered visual planners to broaden these limitations of their training. In this setting, the planner is always achieving stylish success and is influenced by the modern embedded system's design and patterns in the existing method IOT (Internet of thing) based embedded system for PS (Photoshop) course teaching. In the existing method, wireless communication-based image processing is less accurate and less detection of image. So in the proposed method, art design PS (Photoshop) course teaching based FPGA (Field-programmable gate array) and embedded system graphics processing for Image Dissection Algorithm. The state of constant request, finding ways of exposure that lead to development and innovation, which are deeply respected standards for self-assessment. This exploration is based on the architect's perspective and performance observation of the wheels used in visual computerization. Contemporary planning philosophies are fundamentally examined, contradictory, and refined by the mirror action of the scientist. The refined approach to architects helps to advance the method work rehearsals, anticipating the importance of investigation and launch activities. Image Dissection Algorithm Exploration innovations exhibit some contradictions in identified approaches. Like many contemporary creators, they do not adhere to the customer base of expert planning practice, yet modern professionals influence self-produced configuration images. As FPGA (Field-programmable gate array) is confirmed by some parts of the more common planning actions, the expert finds that the architect's involvement with accidental disclosure and innovation has a critical impact on the planning cycle.     

The effects of a group decision support system on culturally diverse and culturally homogeneous group decision making

Considerable research has been conducted over the last decade on the effects of using Group Decision Support Systems (GDSS) in group decision making. Studies have examined the influence of GDSS on such variables as group task, size, quality of decision, and satisfaction with the process. However, only a few studies have focused on the use of GDSS and its interaction with group composition. This study compared the effects of group decision making, both with and without GDSS technology, on culturally diverse and homogeneous groups. Group performance was measured by the number of non-redundant, realistic ideas and the quality of solution produced in response to posed problems. The GDSS used in the study was Vision Quest. Groups using it, regardless of cultural make up, developed a significantly higher number of non-redundant, realistic ideas than groups that did not. Furthermore, among groups using the GDSS, culturally diverse groups produced a significantly higher number of non-redundant, realistic ideas than homogeneous groups that used the GDSS. Implications for diversity management and group support research are suggested.     

The influence of group decision support systems on contribution and commitment levels in multicultural and culturally homogeneous decision-making groups

Research concerning cultural diversity reports that the cultural composition of a group differentially affects group member contribution and commitment levels. In multicultural groups, the majority culture may dominate the decision-making process and ethnic minorities can be perceived to have a lower status due to their position within the social hierarchy. However, research also suggests that group decision making may be structured to promote a more equitable group process. Studies on group decision support systems (GDSS) cite improvements in group processing via the structure and anonymity that can be offered by the technology. This paper presents the results of a pilot study which compared the effects of group decision making, both with and without GDSS technology, on multicultural and homogeneous groups. Findings revealed that both multicultural and homogeneous groups had significantly higher levels of perceived contribution in the GDSS environment. However, there were no significant differences in terms of perceived contribution, commitment, or personal influence between groups in either environment. None the less, all groups achieved a higher number of brainstormed ideas in the GDSS environment. In addition, multicultural groups achieved a statistically higher number of ideas in the GDSS environment in comparison with homogenous groups in the GDSS environment.     

Individual Creativity during the Ideation Phase of Product Innovation: An Interactional Perspective

Although there is increasing acknowledgement that employees' creative ideas are fundamental for product innovation, and many companies use cross‐functional teams to increase employee creativity, there has been little empirical testing of how individual personality and group context interactively affect individual creativity. The purpose of this study is threefold: to examine the relationship between personality and individual creativity; to assess how this relationship interacts with group diversity; and to determine whether the interaction effects between personality traits and gender diversity are mediated by individual knowledge sharing. The results of an experiment based on a sample of 142 working adults show that openness to experience and extraversion are positively related to individual creativity, whereas neuroticism and conscientiousness are negatively related to individual creativity. Furthermore, the impacts of openness to experience and extraversion on individual creativity, respectively, are moderated by both functional diversity and gender diversity. In addition, these interaction effects are mediated by individual knowledge sharing. Interestingly, this study also finds that the direction of functional diversity's moderating effects depends on the level of group diversity.     

Mine,ours, and yours: Whose engagement and prior knowledge affects individual achievement from online collaborative learning?

In computer-supported collaborative learning research, studies examining the combined effects of individual level, group level and within-group differences level measures on individual achievement are scarce. The current study addressed this by examining whether individual, group and within-group differences regarding engagement and prior knowledge predict individual achievement. Engagement was operationalised as group members' exhibited activities in the task space (i.e., discussing domain-content) and social space (i.e., regulating ideas, actions and socioemotional processes). Prior knowledge and achievement were operationalised as group members' performance on a domain-related pre-test and post-test, respectively. Data was collected for 95 triads of secondary education students collaborating on a complex business-economics problem. Subsequently, three different multilevel models were tested to examine the combined effect. First a model with the individual level measures (model 1) was tested and in subsequent models the group level measures (model 2) and within-group levels measures (model 3) were added. Findings indicate model 2 showed the best fit; group members' individual engagement in the social space activities as well as the groups' average prior knowledge positively predicts individual achievement. No effects were found for either group members' or groups' engagement in the task space and for the within-group differences.     

Interview with the drone: experimenting with post-anthropocentric art practice

ABSTRACT

The main idea behind the development of the art project discussed in this artistic contribution, called MNEMODRONE, is to have people share private memories with a drone and then use those memories to create an artificial intelligence. Is it possible for a machine to act based on collective memories? Although there is not a definitive answer, I discuss the ideas behind the project: the problem of quantifying nonhuman forms of consciousness, a model for the drone's artificial intelligence and the advantages of a post-anthropocentric artistic investigation. The second half of my contribution discusses the limits of post-anthropocentric creativity and proceeds more speculatively, proposing a theoretical model of metamorphosis that could be useful for understanding technology and also for artificial intelligent systems to understand humans. My contribution advocates for a creative analysis of future scenarios, both technological and cultural, beyond the boundaries of traditional methodologies. I conclude with a fictional interview that could eventually take place between an interviewer and MNEMODRONE. This fictional interview allows the artwork to speak for itself, and is based on the data collected by the drone in its first year of activities, mimicking its discursive capabilities once the artificial intelligence is fully developed.     

Volumetric Features for Video Event Detection

Real-world actions occur often in crowded, dynamic environments. This poses a difficult challenge for current approaches to video event detection because it is difficult to segment the actor from the background due to distracting motion from other objects in the scene. We propose a technique for event recognition in crowded videos that reliably identifies actions in the presence of partial occlusion and background clutter. Our approach is based on three key ideas: (1) we efficiently match the volumetric representation of an event against oversegmented spatio-temporal video volumes; (2) we augment our shape-based features using flow; (3) rather than treating an event template as an atomic entity, we separately match by parts (both in space and time), enabling robustness against occlusions and actor variability. Our experiments on human actions, such as picking up a dropped object or waving in a crowd show reliable detection with few false positives.     

混合文化优化算法及在车间调度中的应用

针对文化算法收敛速度慢、易陷入局部最优解以及种群多样性少的问题, 本文对文化算法进行优化设计, 提出一种将带有精英保留策略的遗传算法(GA)和模拟退火算法(SA)纳入文化算法(CA)框架的混合优化算法. 此算法基于协同进化的思想, 算法分为下层种群空间和上层信念空间, 两个空间采用了相同的进化机制, 但使用不同的参数. 在文化算法的基础上加入带有精英保留策略的遗传算法, 使种群中的优秀个体直接进入下一代, 以此提高收敛速度; 加入模拟退火算法, 利用其具有突变的特点, 概率性的跳出局部最优并接受劣质解, 以此增加种群多样性. 函数优化结果证明了算法的有效性, 将此算法用于求解最小化最大完工时间的流水车间调度问题, 仿真结果显示, 此算法在收敛速度和精度方面都优于其他几个具有代表性的算法.