Search results

The purpose of this paper is threefold. First, this study seeks to provide a framework for, and endeavor to gain, an in‐depth understanding of the decision‐making process in relation to playing or not playing massively multiplayer online role‐playing games (MMORPGs) by using qualitative data from interviewing both players and non‐players. Second, it seeks to establish a better measure and model using an ethnographic decision tree model that describes the decision‐making process of internet users. Finally, for cross‐validity purposes, it aims to verify the model using quantitative data from face‐to‐face surveys of players/non‐players in an online gaming context.

A two‐phase mixed method is adopted here. During the first phase, the decision tree development phase, to capture the concerns of internet users who are facing the choice of playing MMORPGs or not, qualitative‐based procedures are used to identify decision factors and organize them into a decision tree for better understanding a research problem. In the second phase, the decision tree verification phase, to test the predictive capability of the composite model, a quantitative‐based survey instrument, which represents the decision criteria identified in the first phase, is adopted for data collection and analysis.

The results revealed that 14 criteria, formulated as a decision tree, were identified in the model‐building phase. In the model‐testing phase, 137 decision processes were successfully predicted and 17 predictive pathways led to a decision against the factual, giving a predictive rate of 89 per cent.

The study bridges the gap between the research in online games and in decision making. At the theoretical level, the decision tree model can provide a more comprehensive and in‐depth explanation of the online games‐playing phenomenon. In practice, marketers can easily become aware of the user considerations and identify exactly what needs to be done to fulfil users' criteria for playing MMORPGs. And, from a methodological standpoint, a mixed method can help researchers improve techniques used in study for building more predictive models.

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.

This article aims to describe ethnographic theory and research that maintains the integrity of the individual case while generalizing to multiple cases in research on management decisions. The study aims to provoke and prod management decision researchers to employ ethnographic research tools rather than relying only or mainly on the dominant logic of variable‐based empirical positivism.

Details of two studies of multiple cases in two task environments inform explicit statements of the principles necessary for bridging the gap between management decision practice and research. Six principles serve as pillars for this bridge.

Averages mislead. Partial regression coefficients inform about the impact of variables but mislead in hinting at the sufficiency of individual variables for all cases when high or low values on any one variable are not sufficient or necessary for a high or low outcome on a dependent variable. Research on management decisions must maintain the integrity of the individual case in analyzing and reporting findings on management decisions. Research tools are available now to accomplish these principles.

Get out and into task environments of management decision makers and collect multiple rounds of emic‐etic‐emic‐etic interpretations of management decision processes and outcomes. Go to fsQCA.com to learn how to do qualitative comparative analysis of alternative causal recipes leading to relevant management decision outcomes.

This article describes and calls for a paradigm shift from the current empirical‐positivistic matrix‐algebra dominant logic to a new case‐based Boolean‐algebra logic for management decision researchers.

The general theory of behavioral strategies includes a set of propositions supporting alternative configurations of objectives, contextual features, and beliefs/assessments by executives. The theory includes the outcomes of selections of specific decision alternatives. Building behavioral-strategy models in contexts enriches one or more goals of science and practice: description, understanding, prediction, and influence/control. This chapter is a primer to the general theory. A brief review of relevant empirical studies supports the general theory. The empirical studies include the use of alternative data collection and analytically tools including true field experiments, think aloud methods, long interviews, statistical hypothesis testing, ethnographic decision tree modeling, and building and testing algorithms (e.g., qualitative comparative analysis, QCA). The general theory is the blending of cognitive science, economics, marketing, psychology, and implemented practices in explicit contexts. Consequently, behavioral-strategy theory is distinct from context-free microeconomics, market-driven, and competitor-only decision-making. Capturing and reporting contextually driven alternative routines to strategy setting by a compelling set of propositions represents what is particularly new and valuable about the general theory. The general theory serves as a useful foundation for advances theory and improving the practice of implemented strategies.

The purpose of this paper is to provide instructional guidance on how to increase validity and reduce subjectivity in qualitative studies, such as grounded theory. The paper also demonstrates how different techniques can help management research by including informants/managers in a time efficient way.

This paper describes how three complementary triangulation methods can be used for validation and exploration of concepts and themes in qualitative studies. Tree graphs, concept mapping, and member checking are applied in a managerial case study, complementing a conventional grounded theory approach.

The paper suggests that naturalistic inquiries, such as grounded theory and thematic analysis, can use mixed methods and multiple sources and coders in order to offset biases and to validate and sort findings. The case study presents three different perspectives on how an organization comprehends diversity as a strategic issue.

The paper suggests a mixed methods design that addresses some of the potential shortcomings often found in grounded theory and other qualitative studies, their theory development and their documentation of processes. It positions the approach over the range of the triangulation literature and it argues that it is important to be aware of different triangulation mindsets, and these they are not necessarily contradictory.

This chapter identifies research advances in theory and analytics that contribute successfully to the primary need to be filled to achieve scientific legitimacy: configurations that include accurate explanation, description, and prediction – prediction here refers to predicting future outcomes and outcomes of cases in samples separate from the samples of cases used to construct models. The MAJOR PARADOX: can the researcher construct models that achieve accurate prediction of outcomes for individual cases that also are generalizable across all the cases in the sample? This chapter presents a way forward for solving the major paradox. The solution here includes philosophical, theoretical, and operational shifts away from variable-based modeling and null hypothesis statistical testing (NHST) to case-based modeling and somewhat precise outcome testing (SPOT). These shifts are now occurring in the scholarly business-to-business literature.

Chapter 18 closes the book with twelve principles relevant for doing case study research. The chapter includes brief discussions of specific must-read literature for each principle. The discussion also emphasizes that accuracy (validity) comes first, not generality. The chapter emphasizes that the dominant logic in seeking generality by using surveys whereby informants write-out answers, tick boxes, and never have the opportunity to answer questions that they themselves frame fails to deliver accuracy except possibly when informants are describing evaluating their own recent experiences (see Chapter 2 for further details). The following key thoughts signify the twelve principles:

• •

  Configural not net effects

• •

  Unconscious not conscious thinking

• •

  Dynamic not cross sectional designs

• •

  Multiple routes not one model only

• •

  Predictive validity not only a best fitting model

• •

  Context not context free

• •

  Conjunctive-disjunctive not compensatory decision-making

• •

  Systems thinking not independent versus dependent conditions

• •

  Multi-person not one-person

• •

  Satisfy not optimize decisions

• •

  Unobtrusive evidence not just obtrusive interviews or observations

• •

  Visual not just verbal data collection and interpretation.

Configural not net effects

Unconscious not conscious thinking

Dynamic not cross sectional designs

Multiple routes not one model only

Predictive validity not only a best fitting model

Context not context free

Conjunctive-disjunctive not compensatory decision-making

Systems thinking not independent versus dependent conditions

Multi-person not one-person

Satisfy not optimize decisions

Unobtrusive evidence not just obtrusive interviews or observations

Visual not just verbal data collection and interpretation.

If we are concerned about the imprecision of case studies as research data, we can console ourselves by noting that a man named Darwin was able to write about a study of the Galapagos Islands and a few other cases. To the best of my recollection, there are not statistics in Darwin's book (Simon, 1991, p. 128).

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.