Aim/Purpose: A literature review is often criticized for the absence of coherent construction, synthesis of topics, and well-reasoned analysis. A framework is needed for novice researchers to organize and present information obtained from the literature review. Background: Information and communication technologies advancement have yielded overwhelming information. The massive availability of information poses several challenges, including storage, processing, meaningful organization, and presentation for future consumption. Information System Researchers have developed frameworks, guidelines, and tools for gathering, filtering, processing, storing, and organizing information. Interestingly, information system researchers have vast information that needs meaningful organization and presentation to the research fraternity while conducting a literature review on a research topic. Methodology: This paper describes a framework called LACTiC (Location, Author, Continuum, Time, and Category) that we adapted from another framework called LATCH (Location, Alphabetical, Time, Category, and Hierarchy). LATCH was used to organize and present information on e-commerce websites for seamless navigation. We evaluated the LACTiC framework. Contribution: Information System Researchers can use the LACTiC framework to organize information obtained from literature review. Findings: The evaluation reveals that most researchers from information systems organize information obtained from the literature review category-wise, followed by continuum, author, time, and location. Recommendation for Researchers: Overall, the framework works well and can be helpful for researchers for an initial idea for organizing information obtained from the literature review. Future Research: To conceptualize the framework, the study was carried out using Information Systems related literature. To generalize the proposed framework, we may suggest that the study can be extended to other areas of business management, such as marketing, finance, operation, decision sciences, accounting, and economics.

Aim/Purpose: The Covid-19 pandemic has created many adverse effects. It overloads the healthcare system, causes deaths, and angers some at anti-covid restrictions. This study examines the feasibility of using technical and technological ideas to overcome these effects. The solution is based on new knowledge about the virus, its nature, formation, and activation in the environment. Background: The rapid spread of a new coronavirus infection is taking place against the background of a lack of time required to create new treatment scenarios for the disease, development, production, and vaccine safety research. In such a situation, it became necessary to gain this time for organizing and conducting events that could reduce the burden on the healthcare system. Methodology: The science that studies the morphology, physiology, genetics, ecology, and evolution of viruses is virology. The modern development of virology is moving towards a more accurate and comprehensive description of the mechanisms of interaction of viruses with the host organism. This contributed to the emergence of genomics, transcriptomics, proteomics, and immunomics. However, in virology, there is no particular discipline that sets itself three fundamental goals: to substantiate a single concept of the emergence of viruses; to study the natural mechanisms of formation of virus molecules in the environment; to describe the natural mechanisms of activation of certain viruses in the environment that cause viral pandemics. As a result, there are many articles among the published scientific articles on viruses dealing with the mechanisms of interaction of viruses with the host organism. However, there are no articles on the natural mechanisms of formation and activation of certain viruses in the environment. In the absence of such specialized articles, we were forced to use the method of systems transdisciplinary generalization of disciplinary knowledge to achieve our article’s purpose. Generalization created new knowledge about the nature of viruses, about the mechanisms of their formation and activation in the environment and cells of biological organisms. It is logical to assume that to synchronize the state of biological objects of all functional ensembles on the planet, it is necessary to create and activate appropriate “technological tools.” We have suggested and proved that RNA viruses play the role of such tools. Piezoelectricity activates viruses. It occurs during the compression and stretching of sedimentary rocks and bases of continental plates in different territories. Contribution: The systems transdisciplinary generalization of the knowledge of scientific disciplines made it possible to edit the concept of viruses, to eliminate stereotypes that arose due to the use of unsuccessful analogies. As a result of this generalization, it was possible to prove that viruses are not intracellular parasites. The virus is a “technological tool” of the planetary organizing component. This “tool” aims to correct the genetic programs of organisms of all functional ensembles (plants, animals, people), which will maintain the state of organisms and the parameters of their metabolism in changing environmental conditions. Findings: The viruses that triggered pandemics in the 20th century and early 21st century are RNA viruses. RNA molecules play the role of “technological tools” that the planetary organizing component uses to carry out short-term and long-term adjustments and constant support of the genetic programs of biological organisms. Therefore, in such a situation, it is advisable to talk not about the fight against the virus but only about eliminating the negative manifestations of the Covid-19 pandemic: reducing the number of people in need of emergency hospitalization, eliminating cases of the acute course of the disease and deaths. It is proposed to use certain technical and technological ideas and solutions to eliminate these negative manifestations. Recommendation for Researchers: This paper recommends that researchers use new interdisciplinary and transdisciplinary approaches. They challenge assumptions and conclusions about the nature of viruses, and the mechanisms of their formation and activation in the environment can initiate. Such new research might describe the mechanisms that form and activate viruses in the environment and the body’s cells. They also might provide practical use of this knowledge to eliminate the multiple speculations and fears that arise against the background of reports of the likely appearance of more deadly viruses and viral infections. Future Research: The results of a systems transdisciplinary generalization of disciplinary knowledge about the nature and purpose of viruses are essential for expanding the horizon of the scientific worldview. Future fundamental research on the mechanisms of objective organizing constituents, a general description given in this article, will contribute to a deeper understanding of chemical and biological evolution mechanisms in which modern humanity is involved. In due time, such an understanding will allow a new look at the existing scenarios of the world socio-economic order, explore and describe new principles of sustainable development of society.

Aim/Purpose: The present study aims to frame the relationship between job and personal resources (namely, organizational identification and emotional intelligence), burnout, and musculoskeletal disorders (i.e., back pain, upper limb pain, lower limb discomfort), into the theoretical framework provided by the JD-R health model. Background: Empirical research indicates a connection between burnout and the onset of musculoskeletal problems, one of the most important occupational health issues affecting all jobs and organizations. In light of the JD-R health model, we investigated the association between personal and job resources with burnout and musculoskeletal disorders. Methodology: An anonymous online questionnaire was answered by 320 workers (82.4% female, Mage = 42.18; SDage = 12.24) investigating their perceived level of burnout, the presence of musculoskeletal pain (back, neck, and shoulder), and their level of organizational identification and emotional intelligence. Descriptive analysis, correlation, and moderated mediation model were performed using SPSS. Contribution: We confirmed the role of personal and organizational resources in the salutogenic process considered by the JD-R health model. Emotional intelligence, decreasing the perceived level of burnout, limited the development of musculoskeletal disorders. Moreover, when organizational identification presented low and medium levels, the association between emotional intelligence and burnout strengthened. Findings: Our results showed a negative, indirect effect of emotional intelligence on musculoskeletal disorders via burnout. Moreover, we found a moderation of organizational organization, indicating that at low and medium levels of identification, the association between emotional intelligence and burnout is stronger. Recommendation for Researchers: In addition to work factors involved in the link between burnout and musculoskeletal disorders, it is also important to consider personal and emotional factors, which can decrease the occurrence of adverse consequences. Future Research: Future research developments could contribute to a deeper understanding of the mechanisms linking emotional intelligence, burnout, and musculoskeletal problems, as well as consider objective indicators of burnout levels or consider using ecological data collection methodologies (e.g., ecological momentary assessment), to identify patterns and associations between burnout and musculoskeletal disorders.

Aim/Purpose: The focus on human well-being has attracted the attention of consumers, organizations, and marketers to understand the various facets of Front of Pack Nutrition Labelling (FOPNL). This study examines the overall research trends in the FPONL domain and identifies the new research areas. Background: FOPNL is becoming increasingly popular and its influence has been widely examined. Different label schemes have been introduced across different regions in the world. Nevertheless, such interventions are limited in developing economies. Methodology: This study uses bibliometric analysis methods to explore Front of Pack Nutrition Labelling (FOPNL) trends using 602 articles published in selected business journals. Contribution: The paper identifies the new FOPNL research avenues. The study indicates that FOPNL has become a crucial research area, and more research is needed at the organization, managerial, and policy levels. Findings: The study identifies four themes. The first theme identified is the effect of harmful nutrients on health and the role of FOPNL nutrition in changing eating habits. The second theme focused on the government's policy and implementation of FOPNL nutrition labeling regulations. The third theme is dedicated to the work on attention, perception, understanding, and influence of multiple traffic light schemes. The fourth theme relates to the Health Star Rating, Nutri Score, and Healthier Choice FOPNL nutrition labeling schemes. Overall, the paper informs consumers, manufacturers, and regulators about the recent trends in the FOPNL research. Recommendation for Researchers: Though FOPNL has been widely examined in the health and nutrition domain, however, limited research has been done in the marketing domain. Research using neuroscientific methods (e.g. eye tracking) should provide more robust findings. Future Research: There is limited research on FOPNL from emerging economies. Future research can examine how FOPNL may influence people, policy, and private entities.

Aim/Purpose: In this article, the subjective perspectives of young people in Ghana on the use of digital media are elaborated. The aim is to make the positions of young people visible in the often adult-dominated discourse on digital media and to overcome adult-centered considerations in academic and public debates. In addition, the focus on young people from the Global South is intended to help make their underrepresented voices present in this discourse. Background: Digital media devices and Internet access are conditional on people’s social, economic, and educational participation. Many people in the Global South in particular are not yet granted such access. For children and young people worldwide, the educational opportunities offered by digital media are associated with potential threats to mental health and well-being. However, young people’s views on digital media are rarely addressed, especially in the Global South. Methodology: Based on a qualitative thematic analysis of responses to open-ended questionnaire questions, young Ghanaians’ views on smartphone use and how it affects academic success are examined. Contribution: By focusing on the subjective perspectives of young people, especially from the Global South, voices that have hardly been heard in the discourse on digital media are made audible. This should help overcome the dominant adult-centered perspectives in this discourse. Findings: For young people in Ghana, digital media are part of their everyday lives and often necessary to succeed at school. At the same time, they are concerned about the dangers, e.g., from overuse or cybercrime, for which they have few strategies to deal with. In their answers, they refer to socio-culturally specific discourses and values as well as to generational hierarchies that they perceive and deal with, which go far beyond the topic of digital media use. This makes clear the social tensions in which the debate about digitalization is embedded. Recommendation for Researchers: Young people’s knowledge of and perspectives on digital media is an important resource for learning to use them in an emancipated way. Future Research: Future research should recognize young people as experts in their own right on the issue, explore ways to include their perspectives in the discourse on digital media use and work with them to harness the future potential of the technology and avoid risks.

Aim/Purpose: This study builds upon existing research by investigating the elements contributing to or buffering the onset of burnout symptoms. We examine the relationship between empowering leadership and burnout, considering the concurrent mediation effects of interpersonal workplace conflict, work-home conflict, and support from coworkers. Background: Burnout is a phenomenon that has been widely considered in the scientific literature due to its negative effect on individual and organizational well-being, as well as implications for leadership, coworker support, and conflict resolution. A deeper understanding of burnout prevention strategies across various professional contexts is paramount for enhancing productivity and job satisfaction. Methodology: Using a survey-based cross-sectional design, we employed a combination of Structural Equation Modelling (SEM) and Artificial Neural Network (ANN) to investigate the direct and indirect influences of empowering leadership on four dimensions of employee burnout, mediated by coworker support, interpersonal conflict at work, and work-home conflict. Contribution: This study provides initial insights into the direct and indirect influences of empowering leadership on various dimensions of burnout, highlighting the complex interplay with coworker support, work-home conflict, and workplace interpersonal conflicts. Ultimately, the study provides a comprehensive approach to understanding and mitigating burnout. Findings: Empowering leadership and coworker support can significantly reduce burnout symptoms, while high levels of work-home conflict and interpersonal conflict at work can exacerbate them. Our findings underscore the paramount role of interpersonal conflict in predicting burnout, urging organizations to prioritize resolving such issues for burnout prevention. Recommendation for Researchers: Following our findings, organizations should (a) promote empowering leadership styles, (b) foster coworker support and work-life balance, and (c) address interpersonal conflicts to reduce the likelihood of employee burnout while ensuring that these strategies are tailored to the specific context and culture of the workplace. Future Research: Future research should broaden the exploration of leadership styles’ effects on burnout, identify additional mediators and moderators, expand studies across sectors and cultures, examine differential impacts on burnout dimensions, leverage advanced analytical models, and investigate the nuanced relationship between work contract types and burnout.

Aim/Purpose: Embitterment comprises a stress-related response to unjust life experiences. Studies have found that it can have a toll on employees’ well-being. However, research on this matter is still in its infancy. Background: Within the scope of the present study, Ι sought to investigate how embitterment relates to burnout – the prolonged consequence of stress. This study further explored whether breaches of psychological contracts can trigger embitterment. Methodology: The study employed a cross-sectional design where two hundred and eight (N = 208) participants from the general population completed an online survey. Contribution: Findings suggest that the toll of embitterment might be much more than what research has suggested so far. Those who experience embitterment can become emotionally exhausted and cynical and these findings can be especially useful when identifying embitterment. Findings: It was found that embitterment related to higher burnout levels and more specifically emotional exhaustion and cynicism. No significant findings were revealed for the relationship between professional inefficacy and embitterment. Also, psychological contract breach was found to be a significant predictor of embitterment, supporting further the notion that perceptions of injustice can trigger feelings of embitterment. Results also showed that embitterment mediated the relationship between psychological contract breach and burnout. Recommendation for Researchers: The study highlights the notion that fairness is a key precursor of embitterment, and this finding is essential when developing interventions to prevent embitterment from arising. Future Research: Future research could use a longitudinal study design to unravel whether burnout represents a precondition or the consequence of embitterment. Future research should also include more objective measures. For example, it would be useful to pair self-report data with more objective measures on embitterment (e.g. clinical interviews).

Aim/Purpose: To explore the incidence of addiction potential within the Iranian public working population, describing how many Iranian public employees fall within the diagnostic categories of low, moderate, and high addiction potential. Also, to investigate the predicting role of occupational variables such as perceived stress, job security, and job satisfaction on addiction potential and belonging to low, moderate, and high addiction potential diagnostic categories. Background: Substance addiction among employees can lead to several negative consequences at the individual and organizational levels. Also, it is the fourth cause of death in Iran. However, few studies have been conducted on the topic among employees, and non among Iranian employees. Methodology: The study participants were 430 employees working in governmental offices of the North Khorasan province, Iran. Descriptive statistical analysis and multiple linear regression analysis were conducted to explore the incidence of addiction potential within the analyzed population and to investigate whether occupational variables such as perceived stress, job security, and job satisfaction predicted low, moderate, or high addiction potential. Contribution: This paper suggests that perceived stress might act as a risk factor for developing addiction, whereas job security and job satisfaction might be protective factors against the likelihood of addiction development. Findings: More than half of the sample showed moderate to high addiction potential. Perceived stress was positively related to addiction potential. Job security and job satisfaction were negatively related to addiction potential. Recommendation for Researchers: When addressing the topic of substance addiction, researchers should focus on the preventative side of investigating it; that is, addiction risk rather than already unfolded addiction. Also, researchers should be mindful of the cultural context in which studies are conducted. Future Research: Future research might investigate other relevant occupational predictors in relation to employee addiction potential, such as leadership style, work-life balance, and worktime schedule, or expand on the relevant causal chain by including personality traits such as neuroticism.

Aim/Purpose: The aim of this paper is to examine Gen Z students located in a representative region of the United States when it comes to technology use, news and information gathering behaviors, civic engagement, and social concerns and whether differences exist based on institutional type. The purpose is to report this information so that academics can better understand the behaviors, priorities, and interests of current American students. Background: This paper investigates the mindset of Generation Z students living in the United States during a period of heightened civic unrest. Through the lens of the Theory of Generations, Uses and Gratifications Theory, and Intersectional Theory, this study aims to examine the Gen Z group and compare findings across populations. Methodology: An electronic survey was administered to students from 2019 through 2022. The survey included a combination of multiple responses, Likert scaled, dichotomous, open-ended, and ordinal questions. It was developed in the Survey Monkey system and reviewed by content and methodological experts to examine bias, vagueness, or potential semantic problems. The survey was pilot-tested in 2018 before implementation in order to explore the efficacy of the research methodology. It was then modified accordingly before widespread distribution to potential participants. The surveys were administered to students enrolled in classes taught by the authors, all of whom are educators. Participation was voluntary, optional, and anonymous. Contribution: This paper provides insight into the mindset of Generation Z students living in the United States, which is helpful to members of academia who should be informed about the current generation of students in higher education. Studying Generation Z helps us understand the future and can provide insight into the shifting needs and expectations of society. Findings: According to the findings, Gen Z are heavy users of digital technologies who use social media as their primary source for gathering news about current events as well as information for schoolwork. The majority of respondents considered themselves to be social activists. When institutional type was considered, there were notable differences with the students at the Historically Black College or University (HBCU), noting the greatest concern with a number of pressing issues, including racial justice/Black Lives Matter, women’s rights, gun violence, immigration reform, and human trafficking. Less significance across groups was found when LGBTQIA+ rights and climate change were considered. Recommendation for Researchers: As social media continues to proliferate in daily life and become a vital means of news and information gathering, additional studies such as the one presented here are needed. In other countries facing similarly turbulent times, measuring student interest, awareness, and engagement is highly informative. Future Research: Future research will explore the role that influencers have in opinion formation and the information-gathering habits of Gen Z.

Aim/Purpose: This paper applies informing science principles to analyze the evolution of United States (U.S.) healthcare delivery, exploring how policy shifts, technological advancements, and changing practices have transformed informing processes within this complex system. By examining healthcare delivery through a transdisciplinary lens, we aim to enhance the understanding of intricate informing environments and their dynamics. Background: The U.S. healthcare system epitomizes a complex, evolving transdisciplinary domain intersecting information systems, policy, economics, and public health. Recent transformations in stakeholder information flow necessitate an informing science perspective to comprehend these changes fully. Methodology: We synthesize literature on U.S. healthcare delivery changes, employing informing science frameworks such as Cohen’s “informing environment” concept to analyze the evolution of healthcare informing processes. Contribution: This study expands informing science theory by examining how changes in a complex transdisciplinary system impact information flow, decision-making, and stakeholder interactions. The results provide insights into challenges and opportunities within evolving informing environments. Findings: Our analysis reveals significant alterations in the U.S. healthcare informing landscape due to policy, regulatory, and technological changes. We identify key transformations in client-sender-delivery system relationships, shifts in information asymmetry, and the emergence of novel informing channels and barriers. Recommendation for Researchers: Future studies should develop informing science models capable of capturing the complexity and dynamism of healthcare delivery systems, particularly amidst rapid technological and policy changes. Future Research: Further investigation is needed into how emerging technologies reshape healthcare informing processes and their impact on care quality, accessibility, and cost-effectiveness.

Aim/Purpose: The rise of virtual communication technologies and hybrid work contexts has brought significant changes to leadership dynamics, highlighting the need for effective management of teams operating in both face-to-face and virtual settings, known as hybrid teams. Background: This systematic review examines leadership models utilized in face-to-face and virtual teams, factors contributing to leadership emergence in these contexts, and effective strategies for leading hybrid teams. Methodology: In this study, three scientific databases were searched, resulting in the retrieval of 1,707 studies. These studies were then subjected to a review process following the PRISMA guidelines, ultimately leading to the inclusion of 15 research contributions in the final review. Contribution: Given the results, key strategies for practitioners include the development of strong communication skills, providing constructive feedback, and implementing efficient remote management techniques. Findings: The findings emphasize three prominent leadership models – transformational leadership, leader-member exchange (LMX), and shared leadership – all of which play crucial roles in hybrid team settings. Personality factors drive leadership emergence in face-to-face settings, while virtual settings benefit more from task-related behaviors. Recommendation for Researchers: This review informs researchers seeking to enhance leadership efficacy in modern group settings, aiding leaders in navigating the complexities of hybrid team environments.

Aim/Purpose: This review paper aims to unveil some underlying machine-learning classification algorithms used for political election predictions and how stack ensembles have been explored. Additionally, it examines the types of datasets available to researchers and presents the results they have achieved. Background: Predicting the outcomes of presidential elections has always been a significant aspect of political systems in numerous countries. Analysts and researchers examining political elections rely on existing datasets from various sources, including tweets, Facebook posts, and so forth to forecast future elections. However, these data sources often struggle to establish a direct correlation between voters and their voting patterns, primarily due to the manual nature of the voting process. Numerous factors influence election outcomes, including ethnicity, voter incentives, and campaign messages. The voting patterns of successors in regions of countries remain uncertain, and the reasons behind such patterns remain ambiguous. Methodology: The study examined a collection of articles obtained from Google Scholar, through search, focusing on the use of ensemble classifiers and machine learning classifiers and their application in predicting political elections through machine learning algorithms. Some specific keywords for the search include “ensemble classifier,” “political election prediction,” and “machine learning”, “stack ensemble”. Contribution: The study provides a broad and deep review of political election predictions through the use of machine learning algorithms and summarizes the major source of the dataset in the said analysis. Findings: Single classifiers have featured greatly in political election predictions, though ensemble classifiers have been used and have proven potent use in the said field is rather low. Recommendation for Researchers: The efficacy of stack classification algorithms can play a significant role in machine learning classification when modelled tactfully and is efficient in handling labelled datasets. however, runtime becomes a hindrance when the dataset grows larger with the increased number of base classifiers forming the stack. Future Research: There is the need to ensure a more comprehensive analysis, alternative data sources rather than depending largely on tweets, and explore ensemble machine learning classifiers in predicting political elections. Also, ensemble classification algorithms have indeed demonstrated superior performance when carefully chosen and combined.

Aim/Purpose: The truism is that leadership fosters or restricts innovation behaviours in organisations, but the extent to which it does depends on the leadership style in practice. This study focuses on one of the contemporary leadership styles, knowledge-oriented leadership [KOL], which has received scant attention in research. In doing so, the contextual factors of psychological safety [PS] and employee voice [EV] were applied to determine how KOL influences are channeled to innovation at the individual level. Methodology: Data were collected from 347 academic staff in public universities in Southern Nigeria and subjected to a partial least square [PLS] analytical procedure for data treatment and hypotheses testing using the SmartPLS 3 software for variance-based structural equation modelling. Contribution: The study formed an integrated research framework that links knowledge-oriented leadership and innovation by accounting for the contextual mechanisms of psychological safety and employee voice. Findings: The PLS results demonstrated that the knowledge-oriented leadership and innovation relationship was positive and significant, and this relationship was partially mediated by two variables, namely, PS and EV. Furthermore, the two mediating variables channeled KOL’s influence on innovation in a sequence. Recommendation for Researchers: Organisations need to consider the practical application of KOL to improve innovation outcomes considerably. By this, leadership training programs should include modules, courses, or topics on KOL to engender the formation of requisite managerial skills. More so, they should consider the criterion of demonstrable KOL abilities for leadership selection and recruitment. As a personal development initiative, managers can attend leadership development programmes as well as obtain certification in knowledge management to improve their KOL abilities. This initiative should be encouraged and supported by organisations. In all, the human resource management framework should be responsive to the dynamics of the knowledge economy regarding leadership. Given that PS and EV function as mediators, organisations should actively cultivate an environment enabling interpersonal risky behaviours founded on trust, respect, and cooperation and encourage/support employees who demonstrate such behaviour accordingly. In this line, they should create and sustain a supportive environment that positively reinforces voice decisions and behaviours. Future Research: The study only determined the links between KOL, PS, EV, and innovation in public universities in Southern Nigeria. Other studies may examine the linkages in other knowledge-intensive organisations as well as expand the geographic scope to make for better generality of findings. Future studies should look at other underlying mechanisms that can affect the KOL-innovation relationship, such as psychological capital, work engagement, work commitment, etc. The role of moderators can be identified and introduced to this integrative framework to demonstrate the conditions affecting the linkages.

[Meg O’Neill] 00:08 Hello and welcome to the Berkeley Technology Law Journal podcast. My name is Meg O’Neill and I am one of the editors of the podcast. Today we are excited to share with you a conversation between Berkeley Law LLM student Franco Dellafiori, and Professor Bertrall Ross. Professor ...

The post Berkeley Technology Law Journal Podcast: Will ChatGPT Tell Me How to Vote? Democracy & AI with Professor Bertrall Ross appeared first on Berkeley Technology Law Journal.

An optimisation-based decision-making support is proposed in this study in the form of fuzzy-probabilistic programming, which can be used to solve integrated order allocation, production planning, and inventory management problems in fuzzy and probabilistic uncertain environments. The problem was modelled in an uncertain mathematical optimisation model with two objectives: maximising the expectation of production volume and minimising the expectation of total operational cost subject to demand and other constraints. The model belongs to fuzzy-probabilistic bi-objective integer linear programming, and the generalised reduced gradient method combined with the branch-and-bound algorithm was utilised to solve the derived model. Numerical simulations were performed to illustrate how the optimal decision was formulated. The results showed that the proposed decision-making support was successful in providing the optimal decision with the maximum expectation of the production volume and minimum expectation of the total operational cost. Therefore, the approach can be implemented by decision-makers in manufacturing companies.

Congcong FANG,Yun JIN,Guanlin CHEN,Yunfan ZHANG,Shidang LI,Yong MA,Yue XIE, Vol.E107-D, No.11, pp.1463-1467
Currently, an increasing number of tasks in speech emotion recognition rely on the analysis of both speech and text features. However, there remains a paucity of research exploring the potential of leveraging large language models like GPT-3 to enhance emotion recognition. In this investigation, we harness the power of the GPT-3 model to extract semantic information from transcribed texts, generating text modal features with a dimensionality of 1536. Subsequently, we perform feature fusion, combining the 1536-dimensional text features with 1188-dimensional acoustic features to yield comprehensive multi-modal recognition outcomes. Our findings reveal that the proposed method achieves a weighted accuracy of 79.62% across the four emotion categories in IEMOCAP, underscoring the considerable enhancement in emotion recognition accuracy facilitated by integrating large language models.
Publication Date: 2024/11/01

Takahito YOSHIDA,Takaharu YAGUCHI,Takashi MATSUBARA, Vol.E107-D, No.11, pp.1458-1462
Accurately simulating physical systems is essential in various fields. In recent years, deep learning has been used to automatically build models of such systems by learning from data. One such method is the neural ordinary differential equation (neural ODE), which treats the output of a neural network as the time derivative of the system states. However, while this and related methods have shown promise, their training strategies still require further development. Inspired by error analysis techniques in numerical analysis while replacing numerical errors with modeling errors, we propose the error-analytic strategy to address this issue. Therefore, our strategy can capture long-term errors and thus improve the accuracy of long-term predictions.
Publication Date: 2024/11/01

Keitaro NAKASAI,Shin KOMEDA,Masateru TSUNODA,Masayuki KASHIMA, Vol.E107-D, No.11, pp.1444-1448
To automatically measure the mental workload of developers, existing studies have used biometric measures such as brain waves and the heart rate. However, developers are often required to equip certain devices when measuring them, and can therefore be physically burdened. In this study, we evaluated the feasibility of non-contact biometric measures based on the nasal skin temperature (NST). In the experiment, the proposed biometric measures were more accurate than non-biometric measures.
Publication Date: 2024/11/01

Nan WU,Xiaocong LAI,Mei CHEN,Ying PAN, Vol.E107-D, No.11, pp.1433-1443
With the development of the Semantic Web, an increasing number of researchers are utilizing ontology technology to construct domain ontology. Since there is no unified construction standard, ontology heterogeneity occurs. The ontology matching method can fuse heterogeneous ontologies, which realizes the interoperability between knowledge and associates to more relevant semantic information. In the case of differences between ontologies, how to reduce false matching and unsuccessful matching is a critical problem to be solved. Moreover, as the number of ontologies increases, the semantic relationship between ontologies becomes increasingly complex. Nevertheless, the current methods that solely find the similarity of names between concepts are no longer sufficient. Consequently, this paper proposes an ontology matching method based on semantic association. Accurate matching pairs are discovered by existing semantic knowledge, and then the potential semantic associations between concepts are mined according to the characteristics of the contextual structure. The matching method can better carry out matching work based on reliable knowledge. In addition, this paper introduces a probabilistic logic repair method, which can detect and repair the conflict of matching results, to enhance the availability and reliability of matching results. The experimental results show that the proposed method effectively improves the quality of matching between ontologies and saves time on repairing incorrect matching pairs. Besides, compared with the existing ontology matching systems, the proposed method has better stability.
Publication Date: 2024/11/01

Naoya NEZU,Hiroshi YAMADA, Vol.E107-D, No.11, pp.1408-1421
Modern memory devices such as DRAM are prone to errors that occur because of unintended bit flips during their operation. Since memory errors severely impact in-memory key-value stores (KVSes), software mechanisms for hardening them against memory errors are being explored. However, it is hard to efficiently test the memory error handling code due to its characteristics: the code is event-driven, the handlers depend on the memory object, and in-memory KVSes manage various objects in huge memory space. This paper presents MemFI that supports runtime tests for the memory error handlers of in-memory KVSes. Our approach performs the software fault injection of memory errors at the memory object level to trigger the target handler while smoothly carrying out tests on the same running state. To show the effectiveness of MemFI, we integrate error handling mechanisms into a real-world in-memory KVS, memcached 1.6.9 and Redis 6.2.7, and check their behavior using the MemFI prototypes. The results show that the MemFI-based runtime test allows us to check the behavior of the error handling mechanisms. We also show its efficiency by comparing it to other fault injection approaches based on a trial model.
Publication Date: 2024/11/01

Yuan LI,Tingting HU,Ryuji FUCHIKAMI,Takeshi IKENAGA, Vol.E107-D, No.11, pp.1396-1407
1 millisecond (1-ms) vision systems are gaining increasing attention in diverse fields like factory automation and robotics, as the ultra-low delay ensures seamless and timely responses. Superpixel segmentation is a pivotal preprocessing to reduce the number of image primitives for subsequent processing. Recently, there has been a growing emphasis on leveraging deep network-based algorithms to pursue superior performance and better integration into other deep network tasks. Superpixel Sampling Network (SSN) employs a deep network for feature generation and employs differentiable SLIC for superpixel generation. SSN achieves high performance with a small number of parameters. However, implementing SSN on FPGAs for ultra-low delay faces challenges due to the final layer’s aggregation of intermediate results. To address this limitation, this paper proposes an aggregated to pipelined structure for FPGA implementation. The final layer is decomposed into individual final layers for each intermediate result. This architectural adjustment eliminates the need for memory to store intermediate results. Concurrently, the proposed structure leverages decomposed layers to facilitate a pipelined structure with pixel streaming input to achieve ultra-low latency. To cooperate with the pipelined structure, layer-partitioned memory architecture is proposed. Each final layer has dedicated memory for storing superpixel center information, allowing values to be read and calculated from memory without conflicts. Calculation results of each final layer are accumulated, and the result of each pixel is obtained as the stream reaches the last layer. Evaluation results demonstrate that boundary recall and under-segmentation error remain comparable to SSN, with an average label consistency improvement of 0.035 over SSN. From a hardware performance perspective, the proposed system processes 1000 FPS images with a delay of 0.947 ms/frame.
Publication Date: 2024/11/01

Zhigang WU,Yaohui ZHU, Vol.E107-D, No.11, pp.1385-1395
This article focuses on improving the BiSeNet v2 bilateral branch image segmentation network structure, enhancing its learning ability for spatial details and overall image segmentation accuracy. A modified network called “BiconvNet” is proposed. Firstly, to extract shallow spatial details more effectively, a parallel concatenated strip and dilated (PCSD) convolution module is proposed and used to extract local features and surrounding contextual features in the detail branch. Continuing on, the semantic branch is reconstructed using the lightweight capability of depth separable convolution and high performance of ConvNet, in order to enable more efficient learning of deep advanced semantic features. Finally, fine-tuning is performed on the bilateral guidance aggregation layer of BiSeNet v2, enabling better fusion of the feature maps output by the detail branch and semantic branch. The experimental part discusses the contribution of stripe convolution and different sizes of empty convolution to image segmentation accuracy, and compares them with common convolutions such as Conv2d convolution, CG convolution and CCA convolution. The experiment proves that the PCSD convolution module proposed in this paper has the highest segmentation accuracy in all categories of the Cityscapes dataset compared with common convolutions. BiConvNet achieved a 9.39% accuracy improvement over the BiSeNet v2 network, with only a slight increase of 1.18M in model parameters. A mIoU accuracy of 68.75% was achieved on the validation set. Furthermore, through comparative experiments with commonly used autonomous driving image segmentation algorithms in recent years, BiConvNet demonstrates strong competitive advantages in segmentation accuracy on the Cityscapes and BDD100K datasets.
Publication Date: 2024/11/01

To capture the complexity and diversity of systems with both technical and social features, modelling methods are needed that similarly provide various tools and concepts. Study of developed methods shows that despite all of their advantages and strengths, there is a need for a method that with a holistic approach integrates perspectives, strengths and tools of the developed methods and models with different aspects of socio-technical systems. The main aim of the current study is to design a method for modelling complex socio-technical systems. To achieve this goal, it is necessary to design a method that is based on creativity and existing knowledge base. Therefore, design science research is used as a research strategy to design proposed method. For the first time, design science research in the field of operations research has been used to design a modelling method. This study also presents new tools and concepts for modelling socio-technical systems.

In Italy, the reimbursement provided to healthcare organisations for medical and surgical procedures is based on the diagnosis related group weight (DRGW), which is an increasing function of the complexity of the procedures. This makes the reimbursement an upper unlimited function. This model does not include the relation of the volume with the complexity. The paper proposes a mathematical model for the optimisation of the reimbursement by determining the optimal mix of volume/procedure, considering the relation volume/complexity and DRGW/complexity. The decreasing, linear, and increasing returns to scale have been defined, and the optimal solution found. The comparison of the model with the traditional approach shows that the proposed model helps the healthcare system to discern the quantity of the reimbursement to provide to health organisations, while the traditional approach, neglecting the relation between the volume and the complexity, can result in an overestimation of the reimbursement.

The objective of this study was to explore through the Model of Theory of Planned Behaviour the most important variables that influence the practice of physical and sports activity at home supported by virtual training in the context of the COVID-19 pandemic. A cross-study was proposed between countries from three continents, distributing the questionnaire in Spain (Europe), Pakistan (Asia), and Colombia (South America) to ensure a comprehensive study. The methodology of structural equations using partial least squares was used. The empirical exploratory study supported the hypotheses proposed, with the most important result that confinement due to the COVID-19 pandemic has been a factor causing the practice of physical and sports activity at home. This is one of the first studies to examine sports practice at home and the new context of sports practice that has generated disruptive technologies and the global crisis of the COVID-19 pandemic.

A semantically rich framework to enable real-time knowledge extraction from short length semi-structured documents Lavana Elluri 10:30-11:30 Monday, 4 November 2019, ITE346 Knowledge is currently maintained as a large volume of unstructured text data in books, laws, regulations and policies, news and social media, academic and scientific reports, conversation and correspondence, etc. Most of these […]

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In my knowledge graph class yesterday we talked about the SPARQL query language and I illustrated it with DBpedia queries, including an example getting data about the movie Double Indemnity. I had brought a google assistant device and used it to compare its answers to those from DBpedia. When I asked the Google assistant “Who […]

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Reinforcement Quantum Annealing: A Quantum-Assisted Learning Automata Approach We introduce the reinforcement quantum annealing (RQA) scheme in which an intelligent agent interacts with a quantum annealer that plays the stochastic environment role of learning automata and tries to iteratively find better Ising Hamiltonians for the given problem of interest. As a proof-of-concept, we propose a […]

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Results using the reinforcement learning technique on two SAT benchmarks using a D-Wave 2000Q quantum processor showed significantly better solutions with fewer samples compared to the best-known quantum annealing techniques.

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This paper how to apply dynamic topic models to a set of cybersecurity documents to understand how the concepts found in them are changing over time.

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Basics of the Adtech Ecosystem This guide delves into the intricacies of the adtech ecosystem, an elaborate mesh of platforms and technologies designed to facilitate and enhance the purchase and sale of digital advertising. Within this system, crucial elements such as ad servers, DSPs (Demand Side Platforms), SSPs (Supply Side Platforms), and ad [...]

CEO severance has captured the attention of a wide array of audiences, yet it remains largely unexplored by management scholars. This paper offers a rigorous theoretical examination of CEO severance with the goal of developing a foundation for a systematic research agenda. In particular, we consider if, and how, severance agreements can be effective in serving the interests of both CEOs and shareholders. We argue that severance agreements have potential value as both an executive recruitment and governance tool, but that the way they are conventionally structured undermines the value that shareholders realize from them. The implications of structure have been almost entirely overlooked by scholars, perhaps because the influence of compensation consultants has left little variance in how severance agreements are implemented across firms. We address this gap by theorizing about how severance agreements could be structured to effectively generate value for executives and shareholders. To do this, we introduce a categorization of key dimensions of CEO severance agreements, and consider how each of these dimensions can be structured to facilitate CEO recruiting, while simultaneously mitigating future governance problems. Our propositions offer new opportunities for governance and compensation scholars to link CEO severance agreements to important organizational outcomes.

Drawing on human capital theory, strategy scholars have emphasized firm-specific human capital as a source of sustained competitive advantage. In this study, we begin to unpack the micro-foundations of firm-specific human capital by theoretically and empirically exploring when employees perceive their skills to be firm-specific. We first develop theoretical arguments and hypotheses based on the extant strategy literature, which implicitly assumes information efficiency and unbiased perceptions of firm-specificity. We then relax these assumptions and develop alternative hypotheses rooted in the cognitive psychology literature, which highlights biases in human judgment. We test our hypotheses using two data sources from Korea and the United States. Surprisingly, our results support the hypotheses based on cognitive bias - a stark contrast to the expectations embedded within the strategy literature. Specifically, we find organizational commitment and, to some extent, tenure are negatively related to employee perceptions of the firm-specificity. We also find that employer provided on-the-job training was unrelated to perceived firm-specificity. These findings suggest that firm-specific human capital, as perceived by employees, may drive behavior in ways not anticipated by existing theory - for example, with respect to investments in skills or turnover decisions. This, in turn, may challenge the assumed relationship between firm-specific human capital and sustained competitive advantage. More broadly, our findings may suggest a need to reconsider other theories, such as transaction cost economics, that draw heavily on the notion of firm-specificity and implicitly assume widely shared and unbiased perceptions.

'What's going on?' Within the context of our critically-informed teaching practice, we see moments of deep learning and reflexivity in classroom discussions and assessments. Yet, these moments of criticality are interspersed with surface learning and reflection. We draw on dichotomous, linear developmental, and messy explanations of learning processes to empirically explore the learning journeys of 20 international Chinese and 42 domestic New Zealand students. We find contradictions within our own data, and between our findings and the extant literature. We conclude that expressions of surface learning and reflection are considerably more complex than they first appear. Moreover, developing critical reflexivity is a far more subtle, messy, and emotional experience than previously understood. We present the theoretical and pedagogical significance of these findings when we consider the implications for the learning process and the practice of management education.

Time is inherently present in empirical research on institutional change - most studies sequence actions and events across stages of development, over time. Yet, research has overlooked how temporality, as a negotiated organizing of time, shapes institutional processes, despite that timing, duration, and tenor of relationships are their foundational elements. To unpack the role of temporality in institutions, we examine how actors engage in temporal institutional work - that is, how they construct, navigate, and capitalize on timing norms in their attempts to change institutions. We draw on an inductive study of an institutional project to establish a novel foundation-based university that subsequently came to pace major statewide university reform. We identify three forms of temporal institutional work: entraining - as a top-down, routinized, reproductive form - and constructing urgency, and enacting momentum - both as bottom-up, issue-driven and generative forms. We show that by engaging in these types of work, actors produce windows of opportunity, synchronicity, and irreversibility as shared beliefs about temporality. These beliefs, in turn, shape how the wider institutional change unfolds. Our study shows that temporal institutional work enables institutional change. We discuss the implications for reconceptualizing institutional research from a temporal perspective.

Management educators often assume that research-based arguments ought to be convincing to students. However, college students do not always accept even well-documented research findings. Among the reasons this might happen, we focus on the potential role of psychological mechanisms triggered by scholarly arguments that affect students' self-concepts, leading them to engage in self-enhancing or self-protective responses. We investigated such processes by examining students' reactions to a research argument emphasizing the importance of intelligence to job performance, in comparison to their reactions to research arguments emphasizing the importance of emotional intelligence and/or fit. Consistent with our predictions, students were less likely to accept the argument for the importance of intelligence compared to the alternative, less threatening, arguments (i.e., the importance of emotional intelligence or fit). Further, acceptance of the argument about the importance of intelligence was affected by students' grade point average (GPA) and moderated by their emotional stability. Specifically, consistent with self-enhancement theory, students with lower GPAs were more likely to reject the argument for intelligence and give self-protective reasons for their responses, whereas students with higher GPAs were more likely to accept the argument and give self-enhancing reasons. Implications for future research and for management teaching are discussed.

Building on prior work showing that abusive supervision is a reaction to subordinates' poor performance, we develop a self-control framework to outline when and why supervisors abuse poor performing subordinates. In particular, we argue poor performing subordinates instill in supervisors a sense of hostility towards the subordinate, which in turn leads to engaging in abusive supervision. Within this self-control framework, poor performance is more likely to lead to abusive supervision when (a) the magnitude of the hostility experienced is higher (e.g., for those with a hostile attribution bias), or (b) the translation of hostility into abusive supervision is unconstrained (e.g., for those who are low in trait mindfulness). In two experimental studies with full-time supervisors where we manipulated the independent variable (Study 1) and the mediator (Study 2), and in a multi-wave and multi-source field study with data collected from supervisor-subordinate teams (50 supervisors and 206 subordinates) at two time points (Study 3), we found overall support for our predictions. Implications for how to reduce the occurrence of abusive supervision in the workplace are discussed.

While many studies explain how social science theories shape social reality, few reflect critically on how such theories should shape social reality. Drawing on a new conception of social welfare and focusing on financial regulation, we assess the performative effects of theories on public policy. We delineate how research that focuses narrowly on questions of efficiency and stability reinforces today's technocratic financial regulation that undermines social welfare. As a remedy, we outline how future management research can tackle questions of social justice and thereby promote an inclusive approach to financial regulation that better serves social welfare.

Psychological empowerment has been studied extensively over the past few decades in a variety of contexts and appears to be especially salient within dynamic and complex environments such as healthcare. However, a recent meta-analysis found that psychological empowerment relationships vary significantly across studies, and there is still a rather limited understanding of how empowerment operates across levels. Accordingly, we advance and test a multi-level model of empowerment which seeks to better understand the unique and synergistic effects between unit and individual empowerment in hospital units. Analysis of data involving 544 individuals in 78 units, collected from multiple sources over three different time periods, revealed that unit empowerment evidenced a synergistic interaction with individual-level psychological empowerment as related to individuals' job performance, as well as an indirect effect on performance via individual empowerment, while controlling for previous performance levels. Notably, these effects were significant at relatively high, but not at relatively low levels of unit empowerment. Furthermore, we found that unit voice climate increased unit empowerment and thereby enhanced individual psychological empowerment. These findings suggest that, in complex and dynamic environments, empowering work units is an important means by which leaders can enhance individuals' performance.

Competitive dynamics theory overlooks an entire class of attackers who pose a serious threat to commercial firms—nonmarket players (NMPs) such as activists, environmentalists, social entrepreneurs, and NGOs. Using an institutional perspective, this conceptual manuscript advances competitive dynamics theory by developing a framework of organizational hostility. The framework profiles NMPs according to their propensity to engage firms; it also classifies firms based on their vulnerability and initial reaction to NMP attacks. Corroborated with a mathematical model (Appendix), the conceptual framework explains which NMPs are most hostile to firms; why some NMPs issue threats whereas others quickly strike commercial firms; and which firms are most vulnerable to such hostility.

The interview questions deal with the means by which Estonia and other republics of the former Soviet Union managed to transform their educational systems and the impact of the Soviet heritage on this transformation. An interview was conducted with Professor Olav Aarna. In 1991 Professor Olav Aarna became the rector of TUT. From 2000 to 2003 he held the position of rector of the first private university in Estonia - Estonian Business School (EBS). From 2003 to 2007 Olav Aarna was member of the Estonian Parliament, serving also as Chairman of the Committee for Cultural Affairs responsible for education, research, culture and sports affairs. From 1998-2000 he was Vice Chairman of Estonian National Council for Research and Development. His experience in the field of educational legislation stems from his advisory position to the Minister of Education of Estonia from 1990 to1992. His competence in the field of the Bologna process results from the development of higher education legislation in Estonia (2002-...) and the development of a higher education quality assurance system for Estonia (2008-...). Olav Aarna has consulted third countries in the national qualifications framework (NQF) development as a European Training Foundation (ETF) expert.

Prior research on mergers and acquisitions (M&As) has substantially advanced our understanding of how isolated acquirer- and deal-specific factors affect abnormal returns. However, investors are likely to perceive and evaluate M&As holistically—that is, as complex configurations (i.e., Gestalts) of characteristics, rather than as a list of independent factors. Yet, extant M&A literature has not addressed why and how configurations of factors elicit positive or negative reactions. In other words, overlooking the interdependent nature of factors known to influence acquisition success has limited our understanding of both M&As and investor judgment. Taking an inductive approach to addressing this important issue, this study relies on fuzzy set methodology. Our results provide compelling evidence that investor perceptions of M&A announcements are not only configurational in nature but also characterized by equifinality - or the presence of multiple paths to success - and asymmetric causality - that is, configurations that represent bad deals are not simply a mirror image of good deals, but differ fundamentally. By constructing a typology of "good" and "bad" deals as perceived by market participants, we develop a mid-range theory of M&A stock market performance. As such, this study offers novel theoretical and empirical insights to scholars, and implications for practitioners.

Agency theory-grounded research on boards of directors and firm legitimacy has historically viewed CEO power as de-legitimating, often taking this fact for granted in theorizing about external assessors' evaluations of a firm. With few exceptions, this literature has focused exclusively on capital market participants (e.g., investors, securities analysts) as the arbiters of a firm's legitimacy and has accordingly assumed that legitimate governance arrangements are those derived from the shareholder-oriented prescriptions of agency theory. We extend this line of research in new ways by arguing that customers also externally assess firm legitimacy, and that firms potentially adjust their governance characteristics to meet customers' norms and expectations. We argue that the cultural-cognitive institutions prevalent in customers' home countries influence their judgments regarding a firm's legitimacy, such that firms competing heavily in high-power distance cultures are more likely to have powerful CEOs, with CEO power a source of legitimacy—rather than illegitimacy—among customers. We also argue that the more dependent a firm is on its customers and the more salient cultural power distance is as a demand-side institutional norm, the greater this relationship will be. Data from 151 U.S. semiconductor and pharmaceutical firms over a 10-year period generally support our predictions.

Drawing on theories of behavioral decision making and situational strength, we developed and tested a multilevel model that explains how the performance outcomes of personal initiative tendency depend on the extent of alignment between organizational control mechanisms and proactive individuals' risk propensities. Results from a sample of 383 middle managers operating in 34 business units of a large multinational corporation indicated that risk propensity weakens the positive relationship between personal initiative tendency and job performance. This negative moderating effect was further amplified when middle managers receive high job autonomy but was attenuated in business units with a strong performance management context. We discuss the implications of these findings for research on proactivity, risk taking, and organizational control.

"Best Places to Work" (BPTW) and similar competitions are a proliferating form of third party employment branding. Little is known, however, about how single or repeated third party employment branding occurrences relate to key human capital outcomes. Extending signaling theory by considering signal credibility and comparability, we use archival and survey data from 624 BPTW participants in sixteen competitions across a three-year period to develop and test hypotheses linking BPTW certifications to collective turnover rates and key informant perceptions of applicant pool quality. We find that certifications are associated with lower turnover rates, and in addition, propose competing crystallization and celebrity hypotheses that model turnover trajectories with repeated certifications, finding diminishing marginal turnover reductions across multiple certifications. We also examine company size and industry job opening moderators, finding that as certifications increase, applicant pool quality is (1) higher in smaller companies and (2) higher when job openings are scarcer. Finally, beyond being certified or not, we find supplemental evidence for effects of the specific certification level achieved (e.g., 2nd versus 15th). This investigation advances theory related to collective turnover, applicant pool quality, and employment branding, and is relevant to company decisions about seeking or re-seeking third party certifications.

We argue that employees who perceive that they are provided with a safe climate at work within which to voice their concerns and suggestions about work-related issues or problems will not only be more engaged employees but will also be likely to be more engaged and involved members of their communities. By focusing on the importance of employee voice opportunities, in work organizations, we seek to build our understanding of how to create "positive" organizations that contribute to the building of human potential, both inside the organizational setting and outside in our communities and societies. We also consider how employee voice opportunities in for-profit organizations may be influenced by the law and prevailing attitudes about corporate governance.

As research begins to accumulate on employee volunteering, it appears that this behavior is largely beneficial to employee performance and commitment. It is less clear, however, how employee volunteering is perceived by others in the workplace. Do colleagues award volunteering "credit"- for example, associating it with being concerned about others - or do they "stigmatize" it - for example, associating it with being distracted from work? Moreover, do those evaluations go on to predict how colleagues actually treat employees who volunteer more often? Adopting a reputation perspective, we draw from theories of person perception and attribution to explore these research questions. The results of a field study revealed that colleagues gave credit to employee volunteering when they attributed it to intrinsic reasons and stigmatized employee volunteering when they attributed it to impression management reasons. Ultimately, through the awarded credits, volunteering was rewarded by supervisors (with the allocation of more resources) and coworkers (with the provision of more helping behavior) when it was attributed to intrinsic motives - a relationship that was amplified when stigmas were low and mitigated when stigmas were high. The results of a laboratory experiment further confirmed that volunteering was both credited and stigmatized, distinguishing it from citizenship behavior, which was credited but not stigmatized.

We examine how top management team (TMT) misfit, defined as discrepancies between the TMT's functional roles and the qualifications of the managers who fill those roles, affects the evolution of TMT composition and structure in a longitudinal study of entrepreneurial ventures. We distinguish two types of misfit - overqualification and underqualification - and study how each is associated with TMT changes. We further consider the moderating effect of firm development. Results reveal that underqualified TMTs hire new managers to reinforce existing capabilities whereas overqualified TMTs elaborate their role structures. However, achieving developmental milestones (i.e., obtaining venture capital funding and staging an initial public offering) is a critical contingency to TMT change: absent these milestones, firms neither hire new managers nor add roles, even when they seemingly need to do so. These findings contribute to knowledge of how TMTs and new ventures evolve by underscoring the importance of simultaneously attending to TMT composition and structure.

We study the effects of actors' audience-specific reputations on their levels of success with different audiences in the same field. Extending recent work that has emphasized the presence of multiple audiences with different concerns, we demonstrate that considering audience specificity leads to an improved understanding of reputation effects. Using data on emerging artists in the field of contemporary art from 2001 to 2010, we investigate the manner in which artists' audience-specific reputations affect their subsequent success with two distinct audiences: museums and galleries. Our findings suggest that audience-specific reputations have systematically different effects with respect to success with museums and galleries. Our findings also illuminate the extent to which audience-specific reputations are relevant for emerging research on the contingent effects of reputation. In particular, our findings support our predictions that audiences differ from one another in terms of the extent to which other signals (specifically, status and interaction with other audiences) enhance or reduce the value of audience-specific reputations. Our study thus advances theory by providing empirical evidence for the value of incorporating audience-specific reputations into the general study of reputation.