Regional valuation of infrastructure improvements. The case of Swedish road freight

Is it possible to identify regional differences among shippers in their valuation of infrastructure improvements? The question is analysed within a random utility approach where parameters are estimated by a logit model. Data consists of a Swedish stated preference study from 1992. The results indicate that regional differences may exist but a considerable heterogeneity in the empirical material prohibit robust results in some cases. However, regional differences seem to exist when industrial mix, shipping distance and goods values are held constant. Independent of the limitations, the results should render implications to any infrastructure benefit analysis where parameters from spatial averages are used. The results are based on short term decisions and one should recognise that parameters may vary under mid- and long- term.Regional preferences; road transportation; freight demand; stated preference analysis; random utility models; logit model

Estimation of interregional freight flows with a gravity model by OLS estimation, Poisson and neural network specifications

In this paper we compare three different specifications of gravity models for inter regional freight flow prediction. The most used specification with OLS estimation is compared with a model where data are assumed to be Poisson distributed. We also compare these with a Feed Forward Back Propagation Neural Network. Data consists of freight flows between Norwegian counties. The attribute describing the nodes is population and distance in kilometers gives the friction on transport links. Since we here only are interested in inter regional flows all intra regional flows are excluded. Results are also compared with an earlier study by Bergkvist and Westin (1997) were all data were used. Estimations indicate that OLS compared to Poisson and Neural Network specifications will produce worse predictions. However, the question on how to compare performance is not undisputable and of great importance since different measures can produce quite different results, not just in scale but also in ranking. When non-linear models are used the lack of a simple interpretable R-square measure as in linear regression is evident. We therefore use different measures of performance and discuss their pros and cons. Bergkvist E. and Westin L. (1997) Estimation of gravity models by OLS estimation, NLS estimation, Poisson and Neural Network specifications. Submitted to "Analytical advances in Transportation Systems and Spatial Dynamics." Eds. Gastaldi M. and Reggiani A.

Negative effects of unlabeled response scales

This study used a novel research approach to investigate the effects of unlabeled response scales on response distributions. Instead of responding to standard questionnaire items respondents were asked to report given judgments on either semantic-differential (SD) or agree-disagree (AD) response scales, thereby showing the extent to which respondents agree upon where to place given judgments. Results from a survey-based study ( N = 418) show that respondents to a large extent disagree about where to place judgments on the response scale; the level of agreement for different judgment intensities ranged from 42% to 82% and the level of agreement is lower for AD than SD response scales. The low levels of agreement contribute to non-substantive variance in the data which increases the risk of attenuated or inflated correlations between constructs. Moreover, simulations of actual response distributions suggest that unlabeled response scales may lead to a strong bias in the form of underestimated shares of positive answers. Implications for research and marketing research practice of using unlabeled response scales are discussed and it is recommended that response categories on SD and AD items always should be labeled since this will reduce non-substantive variance and bias in the data

Preregistration as a way to limit questionable research practice in advertising research

© 2020 Advertising Association. This paper discusses two phenomena that threaten the credibility of scientific research and suggests an approach to limiting the extent of their use in advertising research. HARKing (hypothesizing after the results are known) refers to when hypotheses are formulated or modified after the results of a study are known. P-hacking refers to various practices (e.g., adding respondents, introducing control variables) that increase the likelihood of obtaining statistically significant results from a study. Both of these practices increase the risk of false positives (Type I errors) in research results and it is in the interest of the advertising research field that they are limited. Voluntary preregistration, where researchers commit to and register their research design and analytical approach before conducting the study, is put forward as a means to limiting both HARKing and p-hacking

The dynamic nature of marketing constructs

© 2020, Academy of Marketing Science. This study proposes an ideal, four-stage model of construct evolution (emergence → conceptualization → competition → consensus) to explain construct development over time. An in-depth analysis of conceptualizations of two constructs, market orientation (MO) and customer-based brand equity (CBBE), however, reveals different evolutionary stages and trajectories that deviate from the ideal model. The final stage for MO and CBBE is fragmentation, not consensus, characterized by customized operationalizations and variable construct definitions. A supplementary analysis of need for cognition (NFC) and involvement constructs provides additional support. For example, the final stage of NFC is dominance, characterized by nearly complete reliance on standard definitions and operationalizations. Conceptual research, formal measure development, and differing types of constructs all can influence the evolution of constructs. These findings have deep implications for marketing research: Diverse definitions and operationalizations can impede knowledge accumulation. This article proposes guidelines for improving research practices and managing constructs across evolutionary stages

Construct Confusion in Advertising Research

This paper presents results from a study of measurement practice in leading advertising journals. The focus is on heterogeneity in measurement operationalizations, consistency in the naming of constructs, and overlap in the operationalizations of key advertising constructs. These issues were addressed by analyzing the measurement operationalizations of ad credibility and attitude toward the ad (AAd) in all articles published in three leading advertising journals between 2012 and 2014. Results show considerable heterogeneity in the operationalizations of ad credibility, with no studies using the same operationalization. Results also show lacking consistency as different names were used for similar constructs, and that the operationalization of several advertising constructs overlap with AAd. The paper offers a discussion of the implications of this construct confusion for advertising research and suggests steps that can be taken towards improving measurement practice

Construct heterogeneity and proliferation in advertising research

© 2019, © 2019 Advertising Association. This paper presents results from a study of measurement practice in leading advertising journals. The focus is on heterogeneity in measurement operationalizations of the same construct and construct proliferation (i.e. when constructs have different names but overlapping content). These issues were addressed by analyzing the measurement operationalizations in all articles published in three leading advertising journals between 2012 and 2014. Results show considerable heterogeneity in the operationalizations of three common advertising constructs (ad credibility, ad irritation and perceived humour) for which almost every study used a unique operationalization. Results also show considerable construct proliferation as different names were used for the same constructs and there was overlap in the operationalizations of several advertising constructs. The paper offers a discussion of implications for advertising research and suggests steps that can be taken towards improving measurement practice

Cause-related marketing persuasion research: an integrated framework and directions for further research

© 2018, © 2018 Advertising Association. This paper presents an integrative review of the literature on cause-related marketing (CRM) persuasion research (i.e. studies of how CRM influences evaluations of the partner brand). The aim of the study was to review CRM persuasion research and to integrate the findings into a theoretical framework that could direct future research efforts in the area. Drawing on Bergkvist and Taylor\u27s model of Leveraged Marketing Communications (LMC), a dual-path model of CRM persuasion effects was developed. According to the model, CRM affects brand evaluations along two paths: the indirect transfer path which is mediated by attribution of motives and the direct transfer path in which attitude towards the cause is transferred to the brand. The model incorporates results from extant research and provides guidance for future studies

The predictive validity of multiple-item versus single-item measures of the same constructs

This study compares the predictive validity of single-item and multipleitem measures of attitude toward the ad (AAd) and attitude toward the brand (ABrand), which are two of the most widely measured constructs in marketing. The authors assess the ability of AAd to predict ABrand in copy tests of four print advertisements for diverse new products. There is no difference in the predictive validity of the multiple-item and single-item measures. The authors conclude that for the many constructs in marketing that consist of a concrete singular object and a concrete attribute, such as AAd or ABrand, single-item measures should be used

Cut fallow to replace black fallow in an organic production system

Couch grass (Elymus repens) has large impact on yield and management strategies in temperate areas of the world. The control is to a large extent based on repeated soil cultivations in organic farming. Our aim was to investigate methods to improve the competitive effect of white clover by management. The hypothesis was that cutting (fragmentation) of the rhizomes by making slits in the soil by a spade (spading) would increase the number of couch grass shoots, thus improve the effect of repeated mowing. We conclude that Cross cutting to 10 cm could reduce the amount of rhizomes, but that the effect is variable. We also conclude that the cross cutting do not improve the effect of mowing. Cross cutting reduce the amounts of couch grass shoots