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Book part
Publication date: 7 December 2016

Arch G. Woodside

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Case Study Research
Type: Book
ISBN: 978-1-78560-461-4

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Book part
Publication date: 25 July 2017

Arch G. Woodside

Consumer behavior in tourism (CBT) is an interdisciplinary field of study encompassing the basic behavioral and economic sciences (e.g., psychology, sociology, and economics) and…

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Consumer behavior in tourism (CBT) is an interdisciplinary field of study encompassing the basic behavioral and economic sciences (e.g., psychology, sociology, and economics) and applied fields of study (e.g., management, marketing, tourism, and hospitality) focusing on all aspects of discretionary travel. This chapter describes major issues and findings in the literature relating to CBT. The chapter directs the reader’s attention to some of the highly-cited studies in this literature – these studies provide a foundation of knowledge on the central topics, issues, methods, findings, and theoretical/practical contributions in research on CBT. Research studies in CBT focus on one-to-all five core theoretical issues in basic and applied fields of study: describe who is doing what, when, where, how, and the consequences of the activities; explain the meanings of activities and motivations of the actors; predict (model) what actions and outcomes will occur and the impacts of influence attempts before, during, and after engaging in tourist actions; control (influence) the beliefs, attitudes, behaviors, and assessments of tourists, local community members, and additional stakeholders; evaluate tourism service/product delivery, tourism management performance, and customer satisfaction. Survey research using verbal (written) responses to questions is pervasive and the most frequent method for data collection in CBT. Additional research genres in CBT include direct observations of tourism behavior with or without some oral questioning (unobtrusive studies, the long interview method (McCracken, 1988), use of “consumer culture theory”), participant observation including semester abroad and unpaid internships away from home, formal field experiments, and the study of secondary sources (e.g., photographs and writings in blogs and social media (e.g., TripAdvisor) reviews).

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Consumer Behavior in Tourism and Hospitality Research
Type: Book
ISBN: 978-1-78714-690-7

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Book part
Publication date: 27 December 2016

Arch G. Woodside

The introductory chapter includes how to design-in good practices in theory, data collection procedures, analysis, and interpretations to avoid these bad practices. Given that bad…

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The introductory chapter includes how to design-in good practices in theory, data collection procedures, analysis, and interpretations to avoid these bad practices. Given that bad practices in research are ingrained in the career training of scholars in sub-disciplines of business/management (e.g., through reading articles exhibiting bad practices usually without discussions of the severe weaknesses in these studies and by research courses stressing the use of regression analysis and structural equation modeling), this editorial is likely to have little impact. However, scholars and executives supporting good practices should not lose hope. The relevant literature includes a few brilliant contributions that can serve as beacons for eliminating the current pervasive bad practices and for performing highly competent research.

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Bad to Good
Type: Book
ISBN: 978-1-78635-333-7

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Book part
Publication date: 27 December 2016

Arch G. Woodside and Roger Baxter

This chapter points out that the use of a wide range of theoretical paradigms in marketing research requires researchers to use a broad range of methodologies. As an aid in doing…

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This chapter points out that the use of a wide range of theoretical paradigms in marketing research requires researchers to use a broad range of methodologies. As an aid in doing so, the chapter argues for the use of case study research (CSR), defines CSR, and describes several CSR theories and methods that are useful for describing, explaining, and forecasting processes occurring in business-to-business (B2B) contexts. The discussion includes summaries of six B2B case studies spanning more than 60 years of research. This chapter advocates embracing the view that learning and reporting objective realities of B2B processes is possible using CSR methods. CSR methods in the chapter include using multiple interviews (2 + ) separately of multiple persons participating in B2B processes, direct research and participant observation, decision systems analysis, degrees-of-freedom analysis, ethnographic-decision-tree-modeling, content analysis, and fuzzy-set qualitative comparative analysis (fs/QCA.com). The discussion advocates rejecting the dominant logic of attempting to describe and explain B2B processes by arms-length fixed-point surveys that usually involve responses from one executive per firm with no data-matching of firms in specific B2B relationships – such surveys lack details and accuracy necessary for understanding, describing, and forecasting B2B processes.

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Book part
Publication date: 27 December 2016

Arch G. Woodside

This chapter describes tenets of complexity theory including the precept that within the same set of data X relates to Y positively, negatively, and not at all. A consequence to…

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This chapter describes tenets of complexity theory including the precept that within the same set of data X relates to Y positively, negatively, and not at all. A consequence to this first precept is that reporting how X relates positively to Y with and without additional terms in multiple regression models ignores important information available in a data set. Performing contrarian case analysis indicates that cases having low X with high Y and high X with low Y occur even when the relationship between X and Y is positive and the effect size of the relationship is large. Findings from contrarian case analysis support the necessity of modeling multiple realities using complex antecedent configurations. Complex antecedent configurations (i.e., 2–7 features per recipe) can show that high X is an indicator of high Y when high X combines with certain additional antecedent conditions (e.g., high A, high B, and low C) – and low X is an indicator of high Y as well when low X combines in other recipes (e.g., high A, low R, and high S), where A, B, C, R, and S are additional antecedent conditions. Thus, modeling multiple realities – configural analysis – is necessary, to learn the configurations of multiple indicators for high Y outcomes and the negation of high Y. For a number of X antecedent conditions, a high X may be necessary for high Y to occur but high X alone is almost never sufficient for a high Y outcome.

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Bad to Good
Type: Book
ISBN: 978-1-78635-333-7

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Book part
Publication date: 29 January 2018

Arch G. Woodside

Currently, most of the empirical management, marketing, and psychology articles in the leading journals in these disciplines are examples of bad science practice. Bad science…

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Currently, most of the empirical management, marketing, and psychology articles in the leading journals in these disciplines are examples of bad science practice. Bad science practice includes mismatching case (actor) focused theory and variable-data analysis with null hypothesis significance tests (NHST) of directional predictions (i.e., symmetric models proposing increases in each of several independent X’s associates with increases in a dependent Y). Good science includes matching case-focused theory with case-focused data analytic tools and using somewhat precise outcome tests (SPOT) of asymmetric models. Good science practice achieves requisite variety necessary for deep explanation, description, and accurate prediction. Based on a thorough review of relevant literature, Hubbard (2016) concludes that reporting NHST results (e.g., an observed standardized partial regression betas for X’s differ from zero or that two means differ from zero) are examples of corrupt research. Hubbard (2017) expresses disappointment over the tepid response to his book. The pervasive teaching and use of NHST is one ingredient explaining the indifference, “I can’t change just because it’s [NHST] wrong.” The fear of submission rejection is another reason for rejecting asymmetric modeling and SPOT. Reporting findings from both bad and good science practices may be necessary until asymmetric modeling and SPOT receive wider acceptance than held presently.

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Improving the Marriage of Modeling and Theory for Accurate Forecasts of Outcomes
Type: Book
ISBN: 978-1-78635-122-7

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Book part
Publication date: 29 January 2018

Arch G. Woodside, Gábor Nagy and Carol M. Megehee

This chapter elaborates on the usefulness of embracing complexity theory, modeling outcomes rather than directionality, and modeling complex rather than simple outcomes in…

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This chapter elaborates on the usefulness of embracing complexity theory, modeling outcomes rather than directionality, and modeling complex rather than simple outcomes in strategic management. Complexity theory includes the tenet that most antecedent conditions are neither sufficient nor necessary for the occurrence of a specific outcome. Identifying a firm by individual antecedents (i.e., noninnovative vs. highly innovative, small vs. large size in sales or number of employees, or serving local vs. international markets) provides shallow information in modeling specific outcomes (e.g., high sales growth or high profitability) – even if directional analyses (e.g., regression analysis, including structural equation modeling) indicate that the independent (main) effects of the individual antecedents relate to outcomes directionally – because firm (case) anomalies almost always occur to main effects. Examples: a number of highly innovative firms have low sales while others have high sales and a number of noninnovative firms have low sales while others have high sales. Breaking-away from the current dominant logic of directionality testing – null hypothesis significance testing (NHST) – to embrace somewhat precise outcome testing (SPOT) is necessary for extracting highly useful information about the causes of anomalies – associations opposite to expected and “statistically significant” main effects. The study of anomalies extends to identifying the occurrences of four-corner strategy outcomes: firms doing well in favorable circumstances, firms doing badly in favorable circumstances, firms doing well in unfavorable circumstances, and firms doing badly in unfavorable circumstances. Models of four-corner strategy outcomes advance strategic management beyond the current dominant logic of directional modeling of single outcomes.

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Improving the Marriage of Modeling and Theory for Accurate Forecasts of Outcomes
Type: Book
ISBN: 978-1-78635-122-7

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Book part
Publication date: 4 September 2003

Arch G. Woodside and Marcia Y. Sakai

A meta-evaluation is an assessment of evaluation practices. Meta-evaluations include assessments of validity and usefulness of two or more studies that focus on the same issues…

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A meta-evaluation is an assessment of evaluation practices. Meta-evaluations include assessments of validity and usefulness of two or more studies that focus on the same issues. Every performance audit is grounded explicitly or implicitly in one or more theories of program evaluation. A deep understanding of alternative theories of program evaluation is helpful to gain clarity about sound auditing practices. We present a review of several theories of program evaluation.

This study includes a meta-evaluation of seven government audits on the efficiency and effectiveness of tourism departments and programs. The seven tourism-marketing performance audits are program evaluations for: Missouri, North Carolina, Tennessee, Minnesota, Australia, and two for Hawaii. The majority of these audits are negative performance assessments. Similarly, although these audits are more useful than none at all, the central conclusion of the meta-evaluation is that most of these audit reports are inadequate assessments. These audits are too limited in the issues examined; not sufficiently grounded in relevant evaluation theory and practice; and fail to include recommendations, that if implemented, would result in substantial increases in performance.

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Evaluating Marketing Actions and Outcomes
Type: Book
ISBN: 978-0-76231-046-3

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Book part
Publication date: 16 April 2012

Arch G. Woodside, Hugh M. Pattinson and David B. Montgomery

This chapter documents the contributions in the business-to-business (B2B) marketing–buying literature that focus on implemented strategies in specific contexts. Research on…

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This chapter documents the contributions in the business-to-business (B2B) marketing–buying literature that focus on implemented strategies in specific contexts. Research on implemented strategies often includes thick descriptions of how things actually get done over a period of weeks, months, or years including how decision makers make sense of situations, go about processing information, make choices, interact with other decision makers, participate in specific actions, and interpret events and outcomes. Research on implemented strategies favors “direct research” (Mintzberg, 1979) that includes multiple face-to-face interviews of the same and different participants in B2B processes over the course of days, week, months, or years. Direct research is inherently inductive theory-building and case-based data driven in its theory-empirical approach. Direct research includes applying a number of possible research methods and results in a number of advances in B2B implemented-strategy-in-context theory.

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Business-to-Business Marketing Management: Strategies, Cases, and Solutions
Type: Book
ISBN: 978-1-78052-576-1

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Book part
Publication date: 27 December 2016

Arch G. Woodside, Alexandre Schpektor and Richard Xia

This chapter describes the complementary benefits of model-building and data analysis using algorithm and statistical modeling methods in the context of unobtrusive marketing…

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ABSTRACT

This chapter describes the complementary benefits of model-building and data analysis using algorithm and statistical modeling methods in the context of unobtrusive marketing field experiments and in transforming findings into isomorphic-management models. Relevant for marketing performance measurement, case-based configural analysis is a relatively new paradigm in crafting and testing theory. Statistical testing of hypotheses to learn net effects of individual terms in MRA equations is the current dominant logic. Isomorphic modeling might best communicate what executives should decide using the findings from algorithm and statistical models. Data testing these propositions here uses data from an unobtrusive field experiment in a retailing context and includes two levels of expertise, four price points, and presence versus absence of a friend (“pal” condition) during the customer-salesperson interactions (n = 240 store customers). The analyses support the conclusion that all three approaches to modeling provide useful complementary information substantially above the use of one or the other alone and that transforming findings from such models into isomorphic-management models is possible.

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