Innovativeness is one of the fundamental instruments of growth strategies that provide companies with a competitive edge. Only a few recent studies have examined marketing innovation and the factors that might encourage its adoption. This study investigates the factors that motivate marketing innovation and examines whether the occurrence of marketing innovation varies across industry sectors. This study uses data from surveys and a nationwide census conducted by Statistics Canada. They include: the Survey of Innovation and Business Strategies (SIBS) 2009, the Survey of Innovation and Business Strategies (SIBS) 2012, the Business Registry (BR) and the General Index of Financial Information (GIFI). Multilevel (random-intercept) logistic regression modelling is employed. The results show that if a firm has a strategic focus on new marketing practices, maintains marketing within its enterprise, acquires or expands marketing capacity, has competitor and customer orientations, and adopts advanced technology then it is more likely to carry out marketing innovation. However, breadth of long-term strategic objectives and competitive intensity do not have significant impacts on marketing innovation. In addition, product innovation and organizational innovation occur simultaneously with marketing innovation, but process innovation may not. Lastly, the occurrence of marketing innovation is found to vary across industry sectors. The theoretical and empirical implications of the results are discussed within this study.

abstract: Optimal experimental design for generalized linear models is often done using a pseudo-Bayesian approach that integrates the design criterion across a prior distribution on the parameter values. This approach ignores the lack of utility of certain models contained in the prior, and a case is demonstrated where the heavy focus on such hopeless models results in a design with poor performance and with wild swings in coverage probabilities for Wald-type confidence intervals. Design construction using a utility-based approach is shown to result in much more stable coverage probabilities in the area of greatest concern. The pseudo-Bayesian approach can be applied to the problem of optimal design construction under dependent observations. Often, correlation between observations exists due to restrictions on randomization. Several techniques for optimal design construction are proposed in the case of the conditional response distribution being a natural exponential family member but with a normally distributed block effect . The reviewed pseudo-Bayesian approach is compared to an approach based on substituting the marginal likelihood with the joint likelihood and an approach based on projections of the score function (often called quasi-likelihood). These approaches are compared for several models with normal, Poisson, and binomial conditional response distributions via the true determinant of the expected Fisher information matrix where the dispersion of the random blocks is considered a nuisance parameter. A case study using the developed methods is performed. The joint and quasi-likelihood methods are then extended to address the case when the magnitude of random block dispersion is of concern. Again, a simulation study over several models is performed, followed by a case study when the conditional response distribution is a Poisson distribution. / Dissertation/Thesis / Doctoral Dissertation Industrial Engineering 2015

Persönlichkeitsforschung hat innerhalb der letzten Jahrzehnte den Fokus immer mehr von einer Trait- auf eine State-Perspektive verlagert. Psychologische States, einschließlich die der Motivation, werden durch ein komplexes Zusammenspiel von persönlichen Merkmalen und situativen Faktoren beeinflusst. Murray hat bereits 1938 mit seiner Unterscheidung zwischen Need und Press die Bedeutung dieses Zusammenspiels für die Motivationsforschung hervorgehoben, jedoch ist diese grundlegende Idee weitgehend ungeprüft geblieben. Dies liegt nicht zuletzt daran, dass es lange Zeit an Rahmenwerken und Instrumenten fehlte, um die Situation adäquat zu erfassen. Die vorliegende Dissertation konzentriert sich explizit auf Leistungsmotivation und untersucht, wie Variablen der Situationswahrnehmung mit Fluktuationen der Leistungsmotivation zusammenhängen. Zu diesem Zweck werden sowohl ein naturalistisches Design als auch ein Labordesign verwendet. Durch die Untersuchung des Zusammenspiels dieser Konstrukte auf einer hochfrequenten, momentanen Ebene kann Murrays Konzept von Need und Press geprüft werden. In Studie 1 wurde mit Hilfe der Experience Sampling Methode untersucht, ob Leistungsmotivation im täglichen Leben variiert und mit bestimmten Situationswahrnehmungen zusammenhängt. In Studie 2 wurden Random Intercept Cross-Lagged Panel Modelle in einem akademischen Umfeld implementiert, um die Direktionalität des Zusammenhangs zwischen diesen Variablen zu ergründen. Die Ergebnisse zeigten Schwankungen der Leistungsmotivation auf State-Ebene sowie eine erhebliche Kovariation zwischen verschiedenen Konstrukten der Leistungsmotivation und der Wahrnehmung von Duty und Intellect. Die Ergebnisse lieferten zudem vorläufige kausale Belege für die Richtungsabhängigkeit der Beziehung (mit Spillover-Effekten, die hauptsächlich von der Situationswahrnehmung, d. h. Duty, auf Leistungsmotivationsvariablen mit positiver Valenz festgestellt wurden) und stützen damit Murrays Idee von Need und Press. / Personality research has more and more shifted from a trait to a state perspective over the last decades. Psychological states, including motivation, are influenced by a complex interplay of personal characteristics and situational factors. As early as 1938, Murray emphasized the importance of this interaction in the study of motivation with his distinction between need and press, yet this foundational idea has remained largely untested, not least because frameworks and instruments for the assessment of the situation have been lacking for a long time. The present dissertation focuses explicitly on achievement motivation and examines how perceptions of the situation relate to fluctuations in achievement motivation. Both a naturalistic and a laboratory design are utilized. By examining the interplay of these constructs at a highly frequented, momentary level, Murray’s need-press concept can be put to the test. Study 1 used an experience sampling approach to investigate whether achievement motivation varies in daily life and is related to specific situation perceptions. Study 2 implemented random intercept cross-lagged panel models in an academic setting to to fathom the directionality of the link between these variables. Findings revealed fluctuations of achievement motivation at state level as well as substantial covariation of different achievement motivation constructs and the perceptions of Duty and Intellect. Results also offered preliminary causal evidence on the directionality of the relation (with spillover effects that were mainly found from situation perception, that is, Duty, to achievement motivation variables with positive valence), thus supporting Murray’s idea of need and press.

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In this study, a panel data set of flights made by employees at the Royal Institute of Technology (KTH) in Sweden is analyzed using generalized linear modeling approaches, with the aim to create a model with high predictive capability of the quarterly CO2 emission and the number of flights, for a year not included in the model estimation. A Zero-inflated Gamma regression model is fitted to the CO2 emission variable and a Zero-inflated Negative Binomial regression model is used for the number of flights. To build the models, cross-validation is performed with the observations from 2018 as the training set and the observations from the next year, 2019, as the test set. One at a time, the variable that best improves the prediction of the test set data (either as included in the count model or the zero-inflation model) is selected until an additional variable turns out insignificant on a 5% significance level in the estimated model. In addition to the variables in the data, three lags of the dependent variables (CO2 emission and flights) were included, as well as transformed versions of the continuous variables, and a random intercept each for the categorical variables indicating quarter and department at KTH, respectively. Neither model selected through the cross-validation process turned out to be particularly good at predicting the values for the upcoming year, but a number of variables were proven to have a statistically significant association with the respective dependent variable.