Data, measurement, and causal inferences in machine learning: opportunities and challenges for marketing
In: Journal of marketing theory and practice: JMTP, Band 29, Heft 1, S. 65-77
ISSN: 1944-7175
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In: Journal of marketing theory and practice: JMTP, Band 29, Heft 1, S. 65-77
ISSN: 1944-7175
In: Developments in Marketing Science: Proceedings of the Academy of Marketing Science
This volume includes the full proceedings from the 1997 Academy of Marketing Science (AMS) Annual Conference held in Coral Gables, Florida. The research and presentations offered in this volume cover many aspects of marketing science including marketing strategy, consumer behaviour, global marketing, advertising, branding, marketing education, among others. Founded in 1971, the Academy of Marketing Science is an international organization dedicated to promoting timely explorations of phenomena related to the science of marketing in theory, research, and practice. Among its services to membe
In: Developments in Marketing Science: Proceedings of the Academy of Marketing Science
This volume includes the full proceedings from the 1996 Academy of Marketing Science (AMS) Annual Conference held in Phoenix, Arizona. The research and presentations offered in this volume cover many aspects of marketing science including marketing strategy, consumer behaviour, marketing management, international marketing, marketing education, among others. Founded in 1971, the Academy of Marketing Science is an international organization dedicated to promoting timely explorations of phenomena related to the science of marketing in theory, research, and practice. Among its services to membe
In: RAUSP management journal, Band 54, Heft 4, S. 459-489
ISSN: 2531-0488
Purpose
This paper aims to discuss multilevel modeling for longitudinal data, clarifying the circumstances in which they can be used.
Design/methodology/approach
The authors estimate three-level models with repeated measures, offering conditions for their correct interpretation.
Findings
From the concepts and techniques presented, the authors can propose models, in which it is possible to identify the fixed and random effects on the dependent variable, understand the variance decomposition of multilevel random effects, test alternative covariance structures to account for heteroskedasticity and calculate and interpret the intraclass correlations of each analysis level.
Originality/value
Understanding how nested data structures and data with repeated measures work enables researchers and managers to define several types of constructs from which multilevel models can be used.
In: Journal of marketing theory and practice: JMTP, Band 31, Heft 3, S. 261-275
ISSN: 1944-7175
In: The journal of business, Band 50, Heft 1, S. 63
ISSN: 1537-5374
In: The journal of business, Band 50, Heft 2, S. 208
ISSN: 1537-5374
In: Journal of marketing theory and practice: JMTP, S. 1-17
ISSN: 1944-7175
In: European journal of marketing, Band 58, Heft 4, S. 900-927
ISSN: 1758-7123
Purpose
Design is an important construct in the retail environment literature. Yet, the measures used for design have not followed appropriate scale development procedures. The purpose of this study is to provide a conceptual definition and then develop a scale for retail environment design (RED).
Design/methodology/approach
Interviews with both consumers and marketing researchers are used to generate a potential list of items. Using four different studies, these items are refined, and the RED scale is offered.
Findings
This study develops and validates the four-dimensional RED scale to measure the design of retail environments. The dimensions are functional, aesthetic, lighting and signage.
Research limitations/implications
The newly developed RED scale will allow retailing researchers to measure lighting and signage qualities as part of retail design, measure design of retail environments more accurately and allow different studies to be compared.
Practical implications
The newly developed RED scale will allow retailers to better understand customers' perceptions of the four dimensions of design. Retailers spend significant time and money designing and redesigning retail environments. The RED scale will enable managers to ensure these significant investments create competitive advantages and an appropriate return on investment.
Originality/value
A scale to measure retail environment design is developed. The scale includes two dimensions (lighting and signage) that are not typically investigated.
In: RAUSP management journal, Band 54, Heft 4, S. 490-507
ISSN: 2531-0488
Purpose
This paper aims to present the fundamental aspects for the development and validation (D&V) of attitudes' measurement scale, as well as its practical aspects that are not deeply explored in books and manuals. These aspects are the results of a long experience of the authors and arduous learning with errors and mistakes.
Design/methodology/approach
The nature of this paper is methodological and can be very useful for an initial reading on the theme that it rests. This paper presents four D&V stages: literature review or interviews with experts; theoretical or face validation; semantic validation or validation with possible respondents; and statistical validation.
Findings
This is a methodological paper, and its main finding is the usefulness for researchers.
Research limitations/implications
The main implication of this paper is to support researchers on the process of D&V of measurement scales.
Practical implications
Became a step-by-step guide to researchers on the D&V of measurement scales.
Social implications
Support researchers on their data collection and analysis.
Originality/value
This is a practical guide, with tips from seasoned scholars to help researchers on the D&V of measurement scales.
In: Australasian marketing journal: AMJ ; official journal of the Australia-New Zealand Marketing Academy (ANZMAC), Band 27, Heft 3, S. 197-211
ISSN: 1839-3349
Higher-order constructs, which facilitate modeling a construct on a more abstract higher-level dimension and its more concrete lower-order subdimensions, have become an increasingly visible trend in applications of partial least squares structural equation modeling (PLS-SEM). Unfortunately, researchers frequently confuse the specification, estimation, and validation of higher-order constructs, for example, when it comes to assessing their reliability and validity. Addressing this concern, this paper explains how to evaluate the results of higher-order constructs in PLS-SEM using the repeated indicators and the two-stage approaches, which feature prominently in applied social sciences research. Focusing on the reflective-reflective and reflective-formative types of higher-order constructs, we use the well-known corporate reputation model example to illustrate their specification, estimation, and validation. Thereby, we provide the guidance that scholars, marketing researchers, and practitioners need when using higher-order constructs in their studies.
In: Classroom Companion: Business
Partial least squares structural equation modeling (PLS-SEM) has become a standard approach for analyzing complex inter-relationships between observed and latent variables. Researchers appreciate the many advantages of PLS-SEM such as the possibility to estimate very complex models and the method's flexibility in terms of data requirements and measurement specification. This practical open access guide provides a step-by-step treatment of the major choices in analyzing PLS path models using R, a free software environment for statistical computing, which runs on Windows, macOS, and UNIX computer platforms. Adopting the R software's SEMinR package, which brings a friendly syntax to creating and estimating structural equation models, each chapter offers a concise overview of relevant topics and metrics, followed by an in-depth description of a case study. Simple instructions give readers the "how-tos" of using SEMinR to obtain solutions and document their results. Rules of thumb in every chapter provide guidance on best practices in the application and interpretation of PLS-SEM.