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Marketing and technological capabilities are primary drivers of a firm's performance and thus of central interest to managers. Yet the way in which these two capabilities align with changing environments to secure superior performance remains unclear. Drawing on the dynamic capability view and data from a survey of 228 firms, this study proposes a model of how frequent dynamic capability utilization, assessed through its underlying processes of sensing and reconfiguring, relates to marketing and technological capabilities, as well as how market, technological, and competitor turbulence might affect these relationships. The results show that frequent sensing and reconfiguring have stronger positive effects in environments characterized by high competitor turbulence; however, frequent sensing can have negative relationships with marketing and technological capabilities in stable environments. Furthermore, marketing capabilities are positively associated with firm performance in highly competitive environments, whereas technological capabilities enhance performance in stable competitive environments. Keywords Marketing capabilities * Technological capabilities * Marketsensing * Reconfiguring * Dynamic capability * Environmental turbulence * Partial least squares . FIMIX-PLS, Introduction Market-based and technological resources (e.g., brands, IT systems) and capabilities (e.g., marketing expertise, IT maintenance) contribute significantly to a firm's total market capitalization (Ramaswami et al. 2009). Yet valuable [...]

Partial least squares structural equation modeling (PLS-SEM) has become a key multivariate analysis technique that human resource management (HRM) researchers frequently use. While most disciplines undertake regular critical reflections on the use of important methods to ensure rigorous research and publication practices, the use of PLS-SEM in HRM has not been analyzed so far. To address this gap in HRM literature, this paper presents a critical review of PLS-SEM use in 77 HRM studies published over a 30-year period in leading journals. By contrasting the review results with state-of-the-art guidelines for use of the method, we identify several areas that offer room of improvement when applying PLS-SEM in HRM studies. Our findings offer important guidance for future use of the PLS-SEM method in HRM and related fields. [ABSTRACT FROM AUTHOR]

Byline: R. Susan Ellis, Lester W. Johnson, Siegfried P. Gudergan Pre-process, non-queue waiting in service situations is examined to determine its relationship with service satisfaction, using a double disconfirmation model. Three distinct time-related constructs of waiting are utilised: actual, expected and perceived pre-process waiting time. Results of two technology-based experiments that varied actual pre-process waiting time and managed expected pre-process waiting time confirmed the waiting time disconfirmation process and demonstrated a causal effect of that process on overall service perception. Implications for technology environments such as the web are explored.

Byline: Gerhard P. Gudergan, Siegfried P. Gudergan A number of studies from a management perspective distinguish various types and levels of learning. The extent to which actual management decisions take into account such frameworks and lead to innovative services is limited. Increasingly, organisations address these issues by employing system dynamics modelling and simulation (SDMS) with the aim to facilitate learning about industrial service aspects and, ultimately, to offer innovative industrial services. Yet, there is no explicit research assessing the extent to which the employment of SDMS enhances learning in industrial service organisations. The goal of this paper is to investigate this. More specifically, in this paper we link SDMS aspects to critical reflective learning as an antecedent factor of innovation. We provide support for our proposed linkages with a case study, in which we illustrate the effects of SDMS on critical reflective learning within the context of an organisation, which has employed SDMS when developing industrial service strategies.

Commonly used discrete choice model analyses (e.g., probit, logit and multinomial logit models) draw on the estimation of importance weights that apply to different attribute levels. But directly estimating the importance weights of the attribute as a whole, rather than of distinct attribute levels, is challenging. This article substantiates the usefulness of partial least squares structural equation modeling (PLS-SEM) for the analysis of stated preference data generated through choice experiments in discrete choice modeling. This ability of PLS-SEM to directly estimate the importance weights for attributes as a whole, rather than for the attribute's levels, and to compute determinant respondent-specific latent variable scores applicable to attributes, can more effectively model and distinguish between rational (i.e., optimizing) decisions and pragmatic (i.e., heuristic) ones, when parameter estimations for attributes as a whole are crucial to understanding choice decisions. [ABSTRACT FROM AUTHOR]

This research examines whether trust and commitment mediate the extent to which satisfaction influences loyalty, and whether such mediation is conditional on certain demographic or situational customer characteristics. The findings suggest that assuming homogeneity supports the general notion that trust and commitment partially mediate the extent to which satisfaction influences loyalty. FIMIX-PLS and PLS-MGA analyses substantiate that this mediation differs between two distinct customer segments. The two segments reveal heterogeneity in how trust and commitment partially mediate the link between satisfaction and loyalty. That is, the effect of satisfaction on loyalty is fully mediated by trust and commitment in the segment of customers with high education, whereas satisfaction is partially mediated by trust, but not by commitment, in the other segment of customers with less education. [ABSTRACT FROM AUTHOR]