Abstract:This paper discusses the managerial and theoretical implications of model misspecifi cation-specifi cally, formative versus refl ective construct conceptualization, measurement, and modeling of e-service quality. Service quality has a long history of using refl ective indicators in its conceptualization. Recently, researchers have started to question the traditional conceptualization by noting that service quality may be better represented by formative rather than refl ective indicators. We undertook a study o… Show more
“…Two facets of store-related cognitions, namely store atmosphere and service quality perceptions, were included as single-indicant measures in this model because of their formative nature (Collier and Bienstock 2009). The items for these formative measures were first averaged to form composite scores of the facets.…”
Based largely on the recently growing experiential marketing stream, this study explores the joint effects of cognitive assessments of and emotional responses to service experiences on store loyalty in a retail service setting. Experience-related cognitions and store-related cognitions based on evaluations of the service experience, as well as the subsequent positive and negative emotional responses on the part of the customers, are modeled and investigated in terms of effects on store loyalty. Empirical data were collected through a survey of 518 consumers in four coffee shops of two major chains. The results suggest that consumer evaluations of the service experience and store environment may influence store loyalty, both directly and indirectly, through both negative and positive emotional arousals. The relative effects of each construct through different mechanisms are the primary research questions investigated in this study. Managerial implications and future research directions are also discussed.
“…Two facets of store-related cognitions, namely store atmosphere and service quality perceptions, were included as single-indicant measures in this model because of their formative nature (Collier and Bienstock 2009). The items for these formative measures were first averaged to form composite scores of the facets.…”
Based largely on the recently growing experiential marketing stream, this study explores the joint effects of cognitive assessments of and emotional responses to service experiences on store loyalty in a retail service setting. Experience-related cognitions and store-related cognitions based on evaluations of the service experience, as well as the subsequent positive and negative emotional responses on the part of the customers, are modeled and investigated in terms of effects on store loyalty. Empirical data were collected through a survey of 518 consumers in four coffee shops of two major chains. The results suggest that consumer evaluations of the service experience and store environment may influence store loyalty, both directly and indirectly, through both negative and positive emotional arousals. The relative effects of each construct through different mechanisms are the primary research questions investigated in this study. Managerial implications and future research directions are also discussed.
“…). For example, Collier and Bienstock (, pp. 271–272) stated:Numerous studies have conceptualized service quality as an attitude that is based on a reflective judgment.…”
To increase the relevance of logistics and supply chain academic research, this paper recommends the development and testing of middle‐range theory and practice‐level theory. Yet, there are a number of research issues that arise when academic researchers test middle‐range and practice‐level theory, both in measuring constructs and in testing theoretical relationships between constructs. Concerning the measurement of constructs, this paper recommends that academic researchers pay more attention to content validity and undertake rigorous processes to ensure content validity. In addition, academic researchers need to more explicitly define constructs as either reflective or formative. If the construct is defined as formative, then the traditional statistical approaches to validate these measurement scales are not recommended. The appropriate use of employing single‐item measures for concrete constructs is discussed. In regard to conducting hypothesis tests, research issues associated with multicollinearity and omitted variable bias are discussed. Relative weight analysis is ideal for testing theoretical models and research hypotheses when survey data are obtained, multicollinearity is present, and there are a large number of independent variables predicting a dependent variable. Thus, relative weight analysis is ideal for testing research hypotheses in logistics and supply chain management.
“…(1) tangibles, (2) reliability, (3) assurance, (4) empathy, and (5) responsiveness (e.g., Cenfetelli and Bassellier 2009;Collier and Bienstock 2009;Parasuraman et al 1988). Some customers might favor the communication facets (e.g., empathy and responsiveness) when they evaluate service quality, while others might favor the trust facets (e.g., assurance and reliability) in their evaluation.…”
Section: Unobserved Heterogeneity In the Measurement Modelmentioning
A large proportion of information systems research is concerned with developing and testing models pertaining to complex cognition, behaviors, and outcomes of individuals, teams, organizations, and other social systems that are involved in the development, implementation, and utilization of information technology. Given the complexity of these social and behavioral phenomena, heterogeneity is likely to exist in the samples used in IS studies. While researchers now routinely address observed heterogeneity by introducing moderators, a priori groupings, and contextual factors in their research models, they have not examined how unobserved heterogeneity may affect their findings. We describe why unobserved heterogeneity threatens different types of validity and use simulations to demonstrate that unobserved heterogeneity biases parameter estimates, thereby leading to Type I and Type II errors. We also review different methods that can be used to uncover unobserved heterogeneity in structural equation models. While methods to uncover unobserved heterogeneity in covariance-based structural equation models (CB-SEM) are relatively advanced, the methods for partial least squares (PLS) path models are limited and have relied on an extension of mixture regression-finite mixture partial least squares (FIMIX-PLS) and distance measure-based methods-that have mismatches with some characteristics of PLS path modeling. We propose a new method-prediction-oriented segmentation
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