bluuebunny/crossref_metadata_2025_split huggingface dataset:
Noncomparative Scaling Technique
Authors: Swaminathan Vanitha 
Published: December 2010

Abstract
Noncomparative scaling techniques is a set of scaling methods in which each item is scaled independently of each of the others. There are various types of noncomparative scaling techniques such as the graphic rating scale, Likert scale, semantic differential scale, and Stapel scale. In addition to the type of scale, researchers must make decisions regarding the number of scale categories (odd or even), whether to use verbal descriptors along with numbered response categories, balanced versus unbalanced scales, and forced or nonforced responses.
Nonprobability Sampling
Authors: Fox Richard J. 
Published: December 2010

Abstract

Sampling involves selecting a subset from a population to analyze for the purpose of gaining information about the population. When the subset is chosen in a manner that does not involve randomness or chance, the method used to select the sample is called a
nonprobability sampling method
. Estimates derived from such samples may not be representative of the population as a whole. Also, the typical statistical calculations for evaluating the precision of estimates based on the sample are not appropriate when nonprobability sampling is used. In other words, there is no valid margin of error that can be associated with the estimates derived from nonprobability samples. Information derived from nonprobability samples may be useful, but they must be analyzed with caution and a clear understanding of its deficiencies.

The most common nonprobability sampling methods are convenience and self‐selecting samples. As the name suggests, a convenience sample refers to a selection process in which the items selected are convenient to the person conducting the survey, such as university professors conducting research using students in their classes. Self‐selecting samples involve situations in which individuals decide to be included in the sample on their own. Telephone or text polls conducted in conjunction with television shows are good examples of self‐selected sampling. Also, the common “suggestion box” survey is a form of self‐selected sampling.
A general misconception is that making the sample extremely large compensates for any concerns over the fact that nonprobability sampling was used. No matter how large the sample, if it is selected using nonprobability sampling, concerns regarding how well the sample represents the population are valid. Thousands of people may call in to respond in a telephone poll conducted in conjunction with a television show, but the results are still not necessarily representative of the general public.
Confirmatory Factor Analysis
Authors: Fox Richard J. 
Published: December 2010

Abstract

Confirmatory factor analysis is a statistical technique used when investigating the structure of multivariate data. Each of a set of
n
observed variables is represented as a linear combination of
m
(
m
<
n
) unobserved latent variables or factors, plus an independent error term. The
n
×
n
covariance matrix corresponding to the
n
‐dimensional observed variables contains the individual variable variances on the diagonal, and the covariances for all pairs of the individual observed variables in the corresponding off‐diagonal positions. A matrix equation, called the
covariance equation
, relates this
n
×
n
covariance matrix to the matrix whose
n
rows correspond to the coefficients of the
m
latent factors referred to as
factor loadings
, and the covariance matrices of the unobserved latent factors and the errors.

Confirmatory factor analysis is used to test whether a hypothesized structure is appropriate for multivariate data. The hypothesized structure constrains the matrices appearing in the covariance equation. Individual covariances among the latent factors or among the error terms can be assumed equal or set to zero. Likewise, selected variances (diagonal entries) may be presumed to be equal within each of these matrices. Also, selected factor loadings may be set to zero. A random sample of multivariate observations is used to estimate the corresponding sample covariance matrix with and without the constraints imposed by the hypothesized structure. The “constraint free” covariance matrix is the matrix containing the typical sample descriptive statistics. Maximum likelihood estimation is typically used to determine estimates, with the constraints imposed, of the covariance matrices of the latent factors and errors, and the matrix of factor loadings. A statistical test is conducted to determine whether the hypothesized structure fits the data by comparing the sample covariance matrix to its counterpart produced from the covariance equation using the matrices estimated by maximum likelihood (constraints imposed).
Endogeneity
Authors: Arora Neeraj 
Published: December 2010

Abstract

Most regression applications in marketing assume that the independent variables are determined exogenously. This is rarely the case for field data. For example, promotion decisions (
x
) are often impacted by expected sales (
y
) – high potential markets likely get greater resources. Failure to recognize endogeneity in any regression model leads to biased parameter estimates and therefore requires careful attention. Endogeneity could be caused by omitted variables, measurement error, or simultaneity. To address endogeneity, a possible approach is to jointly model demand and marketing variables by recognizing that marketing decisions may be explicitly related to the expected demand or model parameters. Another approach is to include an objective function of the decision maker that incorporates model parameters in the demand equation. An increased recognition of the limitations of a reduced form model that ignores the underlying data‐generating mechanism has led to greater efforts to use structural models that carefully account for endogeneity problems. Data fusion and experiments are also important avenues to account for endogeneity.
Repeated Measures
ANOVA
Authors: Dass Mayukh 
Published: December 2010

Abstract

In marketing research, one of the sources of variability in the observed measures is the respondents themselves. The respondents come from different backgrounds and have unique individual characteristics, and thus can perceive a study differently. Since this sample level variability reduces the effectiveness of the study, it is very important to separate it from the treatment effects and the experimental errors. Unfortunately, these differences among subjects are uncontrolled and are treated as errors in a between‐subject design. Therefore, we use a within‐subject design where the respondents are exposed to more than one treatment condition and hence repeated measures are obtained. Such repeated measures are also necessary in longitudinal studies where respondents are measured at different time periods and in cases where it is difficult to recruit respondents. Traditional analysis of variance (ANOVA) is not adequate to analyze this type of data as it is unable to control the correlation among the repeated measures. Therefore, a different analysis called
repeated measures ANOVA
is used. Repeated measures ANOVA is also considered as an extension of a paired‐sample
t
‐test to a case of more than two related samples.
Consumer Desire
Authors: Bagozzi Richard P. 
Published: December 2010

Abstract
Desires are wants (e.g., “I desire to···”; “I desire···”) or urges or cravings (e.g., “I have a desire to···”; “I have a desire for···”). Desires convert or transform reasons for acting (e.g., anticipated emotions, attitudes, subjective norms) into intentions to act or to achieve a goal. Goal desires motivate goal intentions, action desires motivate behavioral or action intentions. Self‐regulation of decision making and intention formation occurs through the control of one's desires.
Environmental Consumer Behavior
Authors: McCarty John A. , Shrum L. J. , Lowrey Tina M. 
Published: December 2010

Abstract
Environmental consumer behaviors include the extent to which consumers buy environmentally friendly products, and dispose of product waste in an environmentally responsible manner. Polls have shown that a majority of consumers intend to act eco‐friendly; however, their behaviors are not always consistent with their desires. Consumers' reluctance to buying green seems to relate to their perceptions of eco‐friendly products. Green products are perceived as less effective and more expensive than alternatives. Furthermore, consumers are often skeptical of the claims made by environmentally friendly brands.
The extent to which consumers engage in recycling relates to the perceived inconvenience of recycling and consumers' attitudes about the importance of recycling. Research shows that psychographics and personality variables seem to have more impact on recycling attitudes than do demographics such as age and income. In particular, variables that have been shown to be related to recycling include materialism (the extent to which one attaches importance to possessions), collectivism (the extent to which one believes in the importance of the group over the individual), and locus of control (the extent to which people believe that they control their lives rather than that they are controlled by external forces).
Family Life Cycle
Authors: Cole Catherine A. , Nayakankuppam Dhananjay , Sinha Jayati 
Published: December 2010

Abstract
In this article, we review the extant literature on the consumption or family life cycle (FLC). We also review criticisms of this concept. Finally, we propose a framework that might be useful in examining how life cycle might influence household decision making. We report briefly on one subject we have studied in our labs, namely, how children might influence parent preferences.
Implicit Consumer Cognition
Authors: Vargas Patrick T. , Oh Sangdo 
Published: December 2010

Abstract
Implicit consumer cognition may be defined as the unacknowledged or misidentified influence of prior experience on consumer‐related judgment and behavior. Perhaps the most well‐known example of implicit consumer cognition is the movie theater experiment in which the messages “eat popcorn” and “drink Coca‐Cola” were presented subliminally, and caused moviegoers to increase popcorn and soda consumption. The “experiment” was a complete hoax (never happened), but new evidence suggests that subliminally presented stimuli can subtly influence consumer behavior. In this article, we review research on how consumer behavior can be influenced by cognitive processes outside of conscious awareness. We begin by reviewing research on implicit measures of attitudes, in which attitudes are measured indirectly, generally without consumers' awareness that their attitudes are being measured. Implicit measures of attitudes reliably predict behavior, and seem to tap different aspects of attitudes than traditional, explicit measures. We also review research on subliminal persuasion, automatic cognitive processes that can influence consumer behavior (including implicit memory), and touch briefly on consumer behavior that may occur outside of conscious awareness.
Consumer Intentions
Authors: Bagozzi Richard P. 
Published: December 2010

Abstract
An intention is a person's commitment, plan, or decision to carry out an action or achieve a goal. It typically transforms reasons for acting (e.g., attitudes, subjective norms, or motives or desires to act) into action. Implementation intentions involve planning when, where, and how to act. I‐intentions are personal intentions to pursue a goal or perform an action by oneself. Shared or collective intentions exist in the form of either a personal intention to do something with a group of people or contribute to or do one's part of a group activity or in the form of a person concerning oneself as acting together with others to achieve a group end or perform a group goal. The latter is termed a we‐intention.
Emotion
Authors: Ruth Julie A. 
Published: December 2010

Abstract
Emotions are subjective feeling states that are associated with appraisals the consumer makes about a consumption situation. Emotions – including discrete emotions such as pride, or mixed emotions such as the experience of fear, joy, regret, and excitement – arise within many domains of consumer activity. With respect to advertising, upbeat, negative, and warm ad‐evoked emotional responses influence the formation of consumers' ad and brand attitudes. Consumer responses to emotional appeals sometimes produce an inverted U‐shaped pattern of effects, where consumer attitudes are more favorable under moderate compared to low or high levels of the elicited emotion. Regarding decision making, the extent to which a consumer decision maker relies on emotions depends on their heuristic value, representativeness, and relevance. Purchase and service delivery situations, especially negative ones, also elicit emotions with which consumers attempt to cope in a variety of problem‐ or emotion‐focused ways, depending on the emotion and accompanying appraisals. The emotions consumers experience are also influenced by interactions with, and the noninteractive presence of, other people in purchase, service delivery, and other consumption settings, such as gift exchange. Emotions are both affected and influenced by consumers' relationships with family, acquaintances, and service providers.
Consumer Behavior and Services Marketing
Authors: Iacobucci Dawn 
Published: December 2010

Abstract
Services marketing is described with respect to the manner in which it is distinct from marketing goods. The differences are primarily four: (i) services are said to be “simultaneously produced and consumed.” They unfold in real time, and the process gives the marketer more to manage. (ii) Services are characterized as heterogenous. One person's experience of a service encounter may be different from that of another, primarily due to the high component of people involvement in the service deliver–both the frontline employee and the customer himself or herself. (iii) Services are famously intangible. The intangibility leads to challenges in measuring quality and satisfaction. (iv) Services are perishable. Thus planning is required to maximize capacity utilization.
Sustainable Marketing: Collaborating with and Cloning Consumer 3.0
Authors: Honea Heather 
Published: December 2010

Abstract
The degree to which the digital networked environment connects and aggregates individuals has forced the crowd into the marketing equation. The crowd is made up of consumers who both consume and produce (prosumers) and to appropriately integrate them into the marketing process requires a shift in the marketing paradigm. Envisioning integrated marketing communication and brand building as the creation of a marketing ecosystem, where consumer intelligence and production sustains the organization and at the same time supports the prosumers to optimize their consumption decisions, will require a sustainable marketing model.
Sustainable marketing develops long‐term mutually satisfying relationships and co‐prosperity for all stakeholders by collaborating with the audience on the marketing process. Sustainable marketers will have to develop broader perspectives of and deeper insights into prosumers' processing, reactions, and underlying preferences. They will have to build partnership with prosumers to construct relevant marketing narratives and product offerings, inviting all facets of a prosumer's different personas to participate in the development of that narrative.
As individuals chronicle their activities, interests, and actions across the digitally connected universe, ideal material for research, communication, and promotion is offered up freely to marketers by consumers. Developing profiles or consumer clones from such data may offer insights into behavior and choice that consumers could not share, even if they were motivated to do so. To be sustainable, marketers must simply help consumers organize this information in a meaningful manner – assisting consumers in the level, timing, and composition of demand in a way that will help the individual improve consumption behavior as opposed to simply delivering on objectives of the firm. Thus, key aspects of integrated marketing communication will be the re‐education of the consumers about themselves and support for consumers to make best consumption decisions, even if this requires restructuring firm goals.
Sex in Advertising
Authors: Reichert Tom 
Published: December 2010

Abstract
Sex in advertising is a controversial topic in marketing. Types of sexual content typically consist of nudity or physically attractive models in revealing clothing, sexual poses, and other forms of sexual behavior, facilitating factors such as lighting, editing, and sound, and verbal information such as double entendre, suggestive language, or innuendo. Up to 10% of television commercials contain sexual content, compared to a higher proportion in magazine and Internet ads. Research shows that sex in advertising attracts attention, but if its use is not relevant to the product, it can distract viewers from attending to the advertised message and ad sponsor. However, most uses of sex in advertising assert sex‐related outcomes as a result of buying and using the brand (e.g., “I'll be more sexually attractive if I use this fragrance.”). Archaeology discovered early forms of painted murals advertising brothels in ports along the Mediterranean coast. During the modern era, sex in advertising specifically targeted men or women in publications until the 1960s when television commercials reached mass audiences. Sex in advertising is not held in high regard within the advertising profession and its use prompts legitimate criticism regarding the ways in which sexual ads depict women.
Advertising Media Selection and Planning
Authors: Moorman Marjolein , Neijens Peter C. , Smit Edith G. 
Published: December 2010

AbstractReach, frequency, and timing are key concepts in selecting TV, radio, newspapers, magazines, out‐of‐home, direct mail, Internet, and other media for advertising campaigns. We discuss these concepts and their role in media selection and media planning processes. We also describe media and audience factors that influence the impact of media. Finally, we discuss new developments in advertising media.
The Role of Signage in Marketing: Outdoor Advertising, Out‐of‐Home Media, and On‐Premise Signs
Authors: Taylor Charles R. 
Published: December 2010

AbstractSignage plays an important, but often overlooked, role in marketing and advertising. This article focuses on recent findings pertaining to what makes for effective advertising on billboards and other out‐of‐home media. It also discusses the role of on‐premise signs as marketing and advertising devices.
Advertising and the Integrated Marketing Communications (IMC) Process
Authors: Kim Youngseon , Lowrey Tina M. 
Published: December 2010

AbstractIn this cluttered and fragmented media environment, only advertising in traditional media (or a mix of one or two other promotional tools) does not enable marketers to reach their target market. Thus, integrated marketing communications (IMC) are required. IMC involves strategic synchronization of various forms of persuasive communication programs with customers and prospects over time. The goal of IMC is to convey a company's marketing messages in a consistent and coherent manner through different promotional channels. The utmost task for IMC is ensuring consistency in messages and executions so that the target audience is able to connect any execution to the brand in the end.
Database Marketing
Authors: McCarty John A. 
Published: December 2010

AbstractDatabase marketing involves the analysis of customer transaction data, along with other customer information (e.g., demographics), to segment customers and to develop marketing strategies to some or all of those segments. It employs a number of analytical techniques that are used to search for meaningful patterns and relationships in the customer data. Database marketing aids marketers in serving very narrow segments; the information available in databases allows marketers to provide customized marketing strategies to their customers.Database marketing has been used by direct marketers such as catalog marketers for many years; recently, other kinds of firms, such as credit card providers, automobile rental agencies, brick and mortar retailers, casinos, and hotel chains, have found database marketing techniques useful. Charities and associations have also used database marketing. Database marketing is closely aligned with the concept of relationship marketing, focusing on the long‐term relationship with the customer rather than the immediate sales opportunity.
The Advertising Budget
Authors: West Douglas C. 
Published: December 2010

Abstract
The advertising budget is the sum allocated to communications activities in the financial year. Many of the methods used are historic and to a great extent a muddled business reality has been formalized and compartmentalized by researchers. The leading approaches are the judgmental (arbitrary and affordable), the objective and task, measurement (return on investment (ROI), incremental and quantitative models), percentage of sales (percentage last year, percentage anticipated, unit sales), and competitive (competitive absolute, competitive relative). Heuristic methods continue to be popular because they do not put a strain on decision making whereas algorithmic methods, such as the objective and task, can be highly contentious and discordant. Nevertheless there is a certain inherent logic to using heuristic methods as they enable an organization to avoid dysfunctional behavior and to continue to function whether or not the optimal allocation of resources has been made. Furthermore, they make perfect sense when combined with algorithmic methods.
Radical Innovation
Authors: Colarelli O'Connor Gina 
Published: December 2010

Abstract
The phenomenon of innovation has been of interest to management and economics scholars since the disciplines came into existence. Joseph Schumpeter described the process of creative destruction, in which innovations developed and commercialized by small firms cannibalized existing businesses of incumbents as early as 1934. Since then, scholars have elaborated this concept and contrasted it with incremental innovation that develops improvements within defined product arenas and targets them toward defined markets. In this article, the nature of radical innovation is explored. Radical innovations are those that create wholly new markets and/or destroy existing ones, based on technological or logistical breakthroughs. The definitions surrounding this phenomenon are first covered, followed by a discussion of its significance for marketing scholars. The current state of scholarly knowledge regarding radical innovation is described at three levels of analysis: the industry level, the firm level, and the project level. The gaps in our knowledge regarding radical innovation and the opportunities for scholarly work in this field are also discussed.
Innovation Metrics
Authors: Reibstein David , Shankar Venkatesh 
Published: December 2010

Abstract
No firm can last forever on its existing products. It is necessary for a firm to invest for the future through either entirely new products or enhancements of existing products/services. Thus, investments on innovations constitute a major proportion of firms' total investments. To manage their investments in innovation, firms track the success and progress of their innovations. There is a growing body of research on “innovation metrics” – the measures used to track innovation progress. We review the state of the art on innovation metrics, report on the usage of metrics by firms, and highlight the measures that have proven to be most useful to firms.