Miracle-dz/UniFAR-FTUs huggingface dataset:
THE ROLE OF MARKET KNOWLEDGE TYPE ON PRODUCT INNOVATION PERFORMANCE

While it is understood that market knowledge can positively impact product innovation performance (PIP), a better understanding on the nuanced roles of different aspects of market knowledge is needed. More specifically, we aim to gain an understanding of how different types of market knowledge, such as tacit knowledge, are developed and utilised, especially in high uncertainty environments. This research was conducted with a sample of in-depth interviews with industry experts in new product development in the UK grocery sector ([Formula: see text]) followed up by a survey of 193 companies from the UK grocery sector. The study proposes two measures of market information-gathering activities (MIGA) and market knowledge volume informed by input from experts in the UK grocery sector. Results show that MIGA have a positive effect on market knowledge volume and specificity. Market knowledge volume and specificity consequently have a direct effect on PIP. Finally, market knowledge tacitness is positively moderated by market uncertainty. That is, market knowledge tacitness is most impactful in high uncertainty environments, but offers limited benefit in low uncertainty environments. This study provides evidence of how market knowledge-gathering activities and types can positively impact new product performance, especially in high uncertainty environments.
Search Frictions and Evolving Labour Market Dynamics

This paper puts search frictions models under novel empirical scrutiny and tests their ability to match empirical observations. To capture changing dynamics we fit an extended Bayesian time-varying parameter VAR to US labour market data from 1962–2016. Our results indicate that these models are unable to match the responses of key variables to identified structural shocks. We document substantial changes in the transmission, and economic importance, of shocks throughout time that this framework is unable to explain. In particular, although search frictions models use productivity and job separations shocks to explain the labour market, these shocks only explain at best 50% of fluctuations in key labour market variables.
Covariates of face recognition

Face recognition has found several applications ranging from cross border security, surveillance, access c ontrol, multimedia to forensics. Face recognition under variations due to pose, illumination, and expression has been extensively st udied in literature and several approaches have been proposed to address these covariates. Many applications of face recogn ition require matching face images with variations in age and disg uise such as matching a recent photo with your passport image or image on driver’s license. In literature, techniques have a lso been proposed to recognize face images with variations in age and disguise. These challenges can be grouped as existing covariates of face recognition. However, with ever increasing applica tions of face recognition there has emerged a need to understand ne w fascinating challenges in face recognition, emerging covariates of face recognition. Covariates such as forensic sketches, su rgically altered faces, low resolution faces, and look-alikes or twi ns are some of the challenges that have emerged as new covariates of face recognition. These covariates have important law enfo rcement applications; therefore, it has now become imperativefor current face recognition systems to be robust to these chall enges. This report focuses on three different aspects. First, it pr esents a review of different techniques proposed to address thexisting covariates, limitations of current techniques and future scope of advancements. Second, it presents how themerging covariates have evolved, what are the challenges, proposed techniques , and future research directions for each of these covariates. Fi nally, the report presents an evolutionary granular approach to address one of the emerging covariate, plastic surgery.
Effects of stressor congruence with sociotropy-autonomy using a mood induction procedure: a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in Psychology at Massey University

Aaron Beck's cognitive theory of depression suggests that depression results from the activation of underlying dysfunctional attitudes, by a congruent stressor. To test the notion of congruence, thirty-five male and sixty-one female university students were classified as sociotropic or autonomous using the SociotropyAutonomy scale. These subjects took part in a Velten Mood Induction procedure, in which half of the subjects received a congruent negative mood induction, and the other half received an incongruent negative mood induction. The dependent variables of interest were measures of negative affect and of dysfunctional thinking. Although both congruent and incongruent inductions led to an increase in negative affect and in dysfunctional thinking, the most significant increases were observed for the congruent group.
Causes of Bank Suspensions in the Panic of 1893

There are two competing theories explaining bank panics. One argues that panics are driven by real shocks, asymmetric information, and concerns about insolvency. The other theory argues that bank runs are self-fulfilling, driven by illiquidity and the beliefs of depositors. This paper tests predictions of these two theories using information uniquely available for the Crisis of 1893. The results suggest that real economic shocks were important determinants of the location of panics at the national level, however at the local level, both insolvency and illiquidity were important as triggers of bank panics.
Fiscal slack or environmental pressures: which matters more for technological innovation assimilation? A configurational approach

Abstract Prior studies suggest that fiscal slack may positively affect technological innovation in the public sector but yield inconsistency between theoretical expectations and empirical findings. To address this research gap, this study develops a configurational explanation combining fiscal slack and environmental pressures by employing fs-QCA in the context of Chinese provincial governments’ online public service provision. The findings reveal that the role of fiscal slack is environmentally dependent on explaining technological innovation and that environmental pressures seem to be more important. That is, fiscal slack is likely irrelevant to a high degree of technological innovation assimilation, while the demanding environments of multiple environmental pressures matter. Relative fiscal scarcity may be somewhat relevant to a low degree of technological innovation assimilation only when combined with a more relaxed environment. Several theoretical and practical implications are discussed.
Role of External and Domestic Demand in Economic Growth: A Study of BRICS Countries

Abstract Despite the global downturn since 2008, the growth in BRICS countries as a group is least hampered as compared to the growth in the world, in general, and developed countries, in particular. Is it due to the strong domestic demand factors or external factors is an empirical question to be answered. Further, some economists are promulgating for a new development strategy of domestic demand-led growth. Hence, this article tries to examine the role of domestic and external demand to growth in BRICS countries. Domestic investment is taken to explore the impact of domestic demand on growth, while export and import variables are used to investigate the role of external demand in economic growth. To cater to the objective, causality analysis is done among exports, imports, domestic investment and economic growth using the vector auto regression analysis. Generalized impulse response functions are plotted to get an insight of dynamic interrelationships among these variables. The results are country-specific and mixed evidence of export-led and domestic demand-led growth is found depending on the individual countries of BRICS.
Readers, Personal Record Managers, and Community Members: An Exploratory Study of Researchers' Participation in Online Research Information Management Systems

ABSTRACT Prior studies have identified a need for engaging researchers in providing and curating their identity data. This article reports findings from a qualitative study exploring how researchers use and participate in online research information management (RIM) systems and their requirements for information quality in RIM systems. The purpose of the study was to enhance the knowledge of how to design scalable and reliable solutions for research-identity data curation by examining researchers' motivations for participating in online RIM systems and contributing to research-identity data curation. The findings identify nine activity-related motivations for using RIM systems, five types of information-quality problems in RIM systems, and 12 information-quality criteria that researchers perceived to be important in RIM systems. This study also identified three levels of participation in RIM systems: Readers, Personal Record Managers, and Community Members. Design recommendations were suggested for institutional repositories and RIM systems to provide improved services.
Learning from New Literacies

To address the academic and new literacies divide, this study examines the practices and perceived effects of new literacies on academic learning, specific to Asian English major undergraduate language learners. This mixed-methods study reports particularly on the statistical results of a longitudinal survey concerning students’ increasingly digital lives and positive perceptual change (p < 0.05). These results inform how “efficacious learning” mediated by new literacies can transform the academic literacies important for academic success. Their pedagogical implications are discussed.
Leveraging latent structure in high-dimensional data: causality, neuroscience, and nonparametrics

Author(s): Bloniarz, Adam | Advisor(s): Yu, Bin | Abstract: Many scientific fields have been changed by rapid technological progress in data collection, storage, and processing. This has greatly expanded the role of statistics in scientific research. The three chapters of this thesis examine core challenges faced by statisticians engaged in scientific collaborations, where the complexity of the data require use of high-dimensional or nonparametric methods, and statistical methods need to leverage lower dimensional structure that exists in the data. The first chapter concerns the promise and challenge of using large datasets to uncover causal mechanisms. Randomized trials remain the gold-standard for inferring causal effects of treatment a century after their introduction by Fisher and Neyman. In this chapter, we examine whether large numbers of auxilary covariates in a randomized experiment can be leveraged to help improve estimates of the treatment effect and increase power. In particular, we investigate Lasso-based adjustments of treatment effects through theory, simulation, and a case study of a randomized trial of the pulmonary artery cathether. In our investigation, we avoid imposing a linear model, and examine the robustness of Lasso to violations of traditional assumptions.The second chapter examines the use of predictive models to elucidate functional properties of the mammalian visual cortex. We investigate the activity of single neurons in area MT when stimulated with natural video. One way to investigate single-neuron activity is to build encoding models that predict spike rate given an arbitrary natural stimulus. In this work, we develop encoding models that combine a nonlinear feature extraction step with a linear model. The feature extraction step is unsupervised, and is based on the principle of sparse coding. We compare this model to one that applies relatively simple, fixed nonlinearities to the outputs of V1-like spatiotemporal filters. We find evidence that some MT cells may be tuned to more complex video features than previously thought.The third chapter examines a computational challenge inherent in nonparametric modeling of large datasets. Large datasets are often stored across many machines in a computer cluster, where communication between machines is slow. Hence, nonparametric regression methods should avoid communication of data as much as possible. Random forests, among the most popular nonparametric methods for regression, are not well-suited to distributed architectures. We develop a modification of random forests that leverage ideas in nonparametric regression by local modeling. Our method allows for training of random forests completely in parallel, without synchronization between machines, with communication of sufficient statistics at test-time only. We show that this method can improve the predictive performance of standard random forests even in the single-machine case, and that performance remains strong when data is distributed.
Social Networking and Opportunity Recognition: A Focus on Internationalised Firms in South Africa

Social networks serve as an important source for new business opportunities in foreign markets and are considered as one of the most significant resources for the internationalising firm in emerging markets. This article empirically examines how internationalised firms in under-researched African context access and use social networks to increase their recognition of opportunities. Hypotheses are formulated based on several social networking principles and are tested statistically. The findings highlight that interacting with international contacts more fre-quently is associated with higher levels of opportunity recognition when compared to firms with fewer interactions. Additionally, internationalised firms tend to spend more time developing and maintaining contacts which are associated with higher levels of opportunity recognition. The article makes a contribution to the international entrepreneurship literature by demonstrating that multiple social networking factors will raise the level of opportunity recognition for internationalised firms in South Africa.
Moderating Effect of Perceived Organizational Support on Human Resource Development Practices and Organizational Citizenship Behavior

ABSTRACT This study examined the moderating effect of perceived organizational support on the relationship between human resource development practices and organizational citizenship behavior of hotels in Thailand. The results from a survey of 733 frontline employees revealed that the relationship between human resource development practices and organizational citizenship behavior was stronger for employees with the high level of perceived organizational support, compared to employees with the low level of perceived organizational support. Therefore, this finding contributes to a significant understanding of moderating effect of perceived organizational support in service organizations. Discussion and implications are also provided.
Analysis and Mapping of an Updated Terrestrial Heat Flow Data Set

The number of heat flow measurements at the Earth surface has significantly increased since the last global analysis (Pollack et al., 1993, https://doi.org/10.1029/93RG01249), and the most recent of them provide insights into key locations. This paper presents a new compilation, which includes approximately 70,000 measurements. Continental heat flow (67 mWm−2) does not change significantly, but the differences are more important for oceanic heat flow. The divergence with conductive cooling models is reduced significantly for young ages of the seafloor, since the most recent measurements (92 mWm−2) are significantly higher on average than the older ones (79 mWm−2). This is related to a better quality and a better sampling of measurements in regions affected by hydrothermal circulation. The total Earth heat loss derived from these most recent measurements is estimated to ∼40–42 TW and represents only 3–5 TW less than with a conductive cooling model (∼45–47 TW). Hydrothermal heat loss in the oceanic domain is estimated with a new method based on the ruggedness of the seafloor and represents ∼1.5 TW more than previous estimates. The heat flow variability on continents is so large that defining a trend with stratigraphic or tectono‐thermal age is difficult and makes extrapolation from age a poor predictor. On the other hand, additional geological and geophysical information can be combined with age for better predictions. A generalized similarity method was used here to predict heat flow on a global 0.5° × 0.5° grid. The agreement with local measurements is generally good and increases with the number and quality of proxies.
Social Media Shapes Youths Identity and Self Concept in Sawarna, Lebak Banten, Indonesia

This research studies the influence of social media on the development of youth identity and self concept in State High Vocational School SMKN I Bayah, Lebak Banten more deeply. The consumption pattern of social media among adolescents will have effect on the adolescents themselves. In this research the expected effects are at the level of the attitudes effect on the development of identity and self-concept. The message or news content published on social media can affect the attitudes of adolescents, particularly high vocational school students. At first social media is used to establish relationships or connect friendships and information searches, right now the media function has changed the meaning. In some cases, social media can influence audience's attitudes and those towards violent behavior. However, This research examines the positive effects, i.e. the development of adolescents' self-identity and self-concept. This research was conducted using a survey method for high vocational school students SMK I Bayah Banten.
Perceptions and Impact of a Youth-led Childhood Obesity Prevention Intervention among Youth-leaders

ABSTRACT Objective: To evaluate the impact of a youth-led nutrition intervention on youth-leaders themselves Design: Mixed methods, including: in-depth interviews and a quasi-experimental quantitative study comparing youth-leaders and nonparticipant comparison youth Analysis: Qualitative analysis using direct content analysis. Difference-in-differences analyses assessing quantitative program impact. Results: Youth-leaders perceived that the intervention impacted themselves, the youth-participants, and their respective social networks. Youth-leaders experienced greater increases in intentions to eat healthfully (p = .04), and greater decreases in support for healthy eating from their friends (p = .01), than the comparison group. Conclusions/Implications: Youth-leaders reported multiple levels of intervention impact, and increased intentions for healthy eating; however, additional research is needed to enhance impact on behavioral outcomes.
Shoreline Slope Breaks Revise Understanding of Hawaiian Shield Volcanoes Evolution

Slope gradient maps of swath bathymetry around the Hawaiian islands locate 12 shield slope breaks associated with former shorelines that are now submerged, ranging in age back to 5 Ma. The age of their drowning correlates with the waning of tholeiitic shield volcanism that ceases to repave the shoreline sometime between the beginning and the end of the late‐shield stage. Slope breaks on Mauna Loa's northeast and southwest rifts are consistent with it being in the waning stages of shield building. Superposition of shorebreaks shows that the Hualālai shield is older than Mauna Kea's. We find evidence for three volcanic shields forming Ka'ena Ridge, for a simultaneous waning of Maui‐Lāna'i‐Kaho'olawe shield building and the initiation of Kohala shield building by 1.3 Ma, and for Mahukona growing to just above sea level about 0.6 Ma. A contiguous shoreline slope break formed ~1.8 Ma at the end of the West Moloka'i late‐shield stage and the beginning of the East Moloka'i late‐shield stage. At its western end the shield dips obliquely away from, rather than toward, this slope break. Similarly, the short Hualālai slope break plunges north, which is opposite to that expected for volcanic loading to the south. Shields locally sloping away from paleoshorelines may be related to landslides causing flexural back tilting away from their unloaded footwall. The Nu'uanu and Wailau slides and Pololū slump were mostly shield flank events that cut marginally into their former shorelines, enough to preferentially nucleate headward erosion by streams.
Anticipated Regret and Equity Returns

We investigate the cross-sectional asset pricing implications of anticipated regret for mean-variance investors. We propose a theoretical framework in which mean-variance investors anticipate regret due to deviations from the best possible return-volatility combination, i.e., the highest Sharpe ratio. We show that equity portfolios with high anticipated regret generate 7.6% more annualized alpha than portfolios with low anticipated regret. The significantly positive anticipated regret premium is not explained by costly arbitrage, investor inattention, prospect theory, post-earnings-announcement drift, and neither is spanned by established risk and behavioral factors that have been documented to be robust predictors of the cross-section of equity returns.
Societal Ethics and Social Entrepreneurship: A Cross-Cultural Comparison

Using multilevel modeling and data from 26 countries that include 93,439 individual-level responses on social entrepreneurship for the year 2015, we seek to understand how societal-level ethical orientations impact the likelihood of individuals engaging in social entrepreneurship. We develop a multidimensional representation of societal ethics, in that we draw close parallels between the three institutional pillars—normative, cognitive, and regulatory—with three forms of ethics and use this understanding to predict their effects on the demand for and supply of social entrepreneurs. We find that low behavioral ethics (normative ethics) at the societal level provides opportunities for individuals to become social entrepreneurs. Furthermore, while unselfishness (cognitive ethics) motivates individuals to become social entrepreneurs, high public-sector ethics (regulatory ethics) provides the institutional support for such entrepreneurs to thrive. We contribute to cross-cultural comparative entrepreneurship by providing ethical antecedents of social entrepreneurship through a deeper understanding of the influence of ethics as national-level institutions.
Antecedents of brand loyalty in the fashion industry of Pakistan: Moderating effect of Individual-level collectivist values

The main purpose of this research was to find the moderation effect of individual-level collectivist values on the antecedents of Brand loyalty (BL). What effect does consumer difference on low or high collectivist values have on the brand loyalty in the fashion apparels? It has been found that both groups of consumers have different choices while buying. To investigate this, Individual Level and three antecedent’s promotion (PRO), perceived brand quality (PBQ), and brand trust (BT) were selected to check the effect on Brand Loyalty. The questionnaire was self-developed and distributed online on social networking sites through a non-restricted non-probability sampling technique among 201 Pakistani respondents. Path Analysis and SEM analysis was performed to check the moderation in AMOS. This study has developed and tested the theory by finding that individual-level collectivist values (ILCV) have a significant moderating effect on the relationship between PBQ and BL. The findings reveal that consumers low in ILCV become significantly more loyal to a brand, particularly when PBQ is relatively at high levels. The main contribution of the study is that it presents the validated brand loyalty model with the interaction of ILCV.