Wold’s (1974; 1982) partial least squares structural equation modeling (PLS-SEM) ap-proach and the advanced PLS-SEM algorithms by Lohmoller (Lohmoller 1989) have enjoyed steady popularity as a key multivariate analysis methods in management infor-mation systems (MIS) research (Gefen et al. 2011). Chin’s (1998b) scholarly work and technology acceptance model (TAM) applications (e.g., Gefen and Straub 1997) are milestones that helped to reify PLS-SEM in MIS research. In light of the proliferation of SEM techniques, Gefen et al. (2011), updating Gefen et al. (2000), presented a compre-hensive, organized, and contemporary summary of the minimum reporting requirements for SEM applications. Such guidelines are of crucial importance for advancing research for several reasons. First, researchers wishing to apply findings from prior studies or wanting to contribute to original research must comprehend other researchers’ decisions in order to under-stand the robustness of their findings. Likewise, when studies arrive at significantly different results, the natural course is to attempt explaining the differences in terms of the theory or concept employed, the empirical data used, and how the research method was applied. A lack of clarity on these issues, including the methodological applications, contradicts the goals of such studies (Jackson et al. 2009). Even worse, the misapplication of a technique may result in misinterpretations of empirical outcomes and, hence, false conclusions. Against this background, rigorous research has a long-standing tradition of critically reviewing prior practices of reporting standards and research method use (e.g., Boudreau et al. 2001). While the use of covariance-based SEM (CB-SEM) techniques has been well documented across disciplines (e.g., Medsker et al. 1994; Shook et al. 2004; Steenkamp and Baumgartner 2000), few reviews to date have investigated usage practices specific to PLS-SEM (see, however, Gefen et al. 2000). Previous reviews of such research practices were restricted to strategic management (Hulland 1999) and, more recently, marketing (Hair et al. 2012; Henseler et al. 2009), and accounting (Lee et al. 2011). The question arises as to how authors publishing in top IS journals such as MIS Quarterly have used PLS-SEM thus far, given the SEM recommendations of Gefen et al. (2011). By relating Gefen et al.’s (2011) reporting guidelines to actual practice, we attempt to identify potential problematic areas in PLS-SEM use, problems which may explain some of the criticism of how it has been applied (e.g., Marcoulides et al. 2009; Marcoulides and Saunders 2006). By reviewing previous PLS-SEM research in MIS Quarterly, we can hopefully increase awareness of established reporting standards. The results allow researchers to further improve the already good reporting practices that have been established in MIS Quarterly and other top journals and thus could become blueprints for conducting PLS-SEM analysis in other disciplines such as strategic management and marketing.

https://papers.ssrn.com/sol3/Delivery.cfm/SSRN_ID2224526_code1463265.pdf?abstractid=2176426&type=2

A critical look at the use of PLS-SEM in MIS Quarterly

Hawaii International Conference on System Sciences

Human life is dependent upon the natural environment, which, most would agree, is rapidly degrading. Business enterprises are a dominant form of social organization and contribute to the worsening, and enhancement, of the natural environment. Scholars in the administrative sciences examine questions spanning organizations and the natural environment but have largely omitted the information systems perspective. We develop a research agenda on information systems innovation for environmental sustainability that demonstrates the critical role that IS can play in shaping beliefs about the environment, in enabling and transforming sustainable processes and practices in organizations, and in improving environmental and economic performance. The belief-action-outcome (BAO) framework and associated research agenda provide the basis for a new discourse on IS for environmental sustainability.

https://misq.org/downloadable/download/linksample/link_id/838/in

Information systems innovation for environmental sustainability

Lindell and Whitney introduced a partial correlation technique, now referred to as the correlational marker technique, for controlling method variance using a marker variable that is theoretically unrelated to substantive variables in a study. This article (a) first reviews their specific analysis plan, and then (b) reviews empirical studies that have followed all or part of this plan. The authors also (c) describe a structural equation method that has been applied to the analysis of marker variables and (d) review empirical studies using this analytical approach. Next, the authors (e) develop a comprehensive confirmatory factor analysis (CFA) marker technique analysis plan, and (f) demonstrate this plan with an empirical example. Finally, the authors (g) describe how marker variables can be examined along with other method variance processes, (h) discuss the important role of theory in the critical step of selecting marker variables, and (i) discuss assumptions and limitations of the Comprehensive CFA Ma...

Method Variance and Marker Variables: A Review and Comprehensive CFA Marker Technique

Recommendation agents (RAs) are software agents that elicit the interests or preferences of individual consumers for products, either explicitly or implicitly, and make recommendations accordingly RAs have the potential to support and improve the quality of the decisions consumers make when searching for and selecting products online They can reduce the information overload facing consumers, as well as the complexity of online searches Prior research on RAs has focused mostly on developing and evaluating different underlying algorithms that generate recommendations This paper instead identifies other important aspects of RAs, namely RA use, RA characteristics, provider credi'r, and user-RA interaction, which influence users' decision-making processes and outcomes, as well as their evaluation of RAs It goes beyond generalized models, such as TAM, and identifies the RA-specific features, such as RA input, process, and output design characteristics, that affect users' evaluations, including their assessments of the usefulness and ease-of-use of RA applications

Based on a review of existing literature on e-commerce RAs, this paper develops a conceptual model with 28 propositions derived from five theoretical perspectives The propositions help answer the two research questions: (1) How do RA use, RA characteristics, and other factors influence consumer decision making processes and outcomes? (2) How do RA use, RA characteristics, and other factors influence users' evaluations of RAs? By identifying the critical gaps between what we know and what we need to know, this paper identifies potential areas of future research for scholars It also provides advice to information systems practitioners concerning the effective design and development of RAs

E-commerce product recommendation agents: use, characteristics, and impact

An electronic commerce marketing channel is fully mediated by information technology, stripping away much of a product's physical informational cues, and creating information asymmetries (i.e., limited information). These asymmetries may impede consumers' ability to effectively assess certain types of products, thus creating challenges for online sellers. Signaling theory provides a framework for understanding how extrinsic cues ᾢ signals ᾢ can be used by sellers to convey product quality information to consumers, reducing uncertainty and facilitating a purchase or exchange. This research proposes a model to investigate website quality as a potential signal of product quality and consider the moderating effects of product information asymmetries and signal credibility. Three experiments are reported that examine the efficacy of signaling theory as a basis for predicting online consumer behavior with an experience good. The results indicate that website quality influences consumers' perceptions of product quality, which subsequently affects online purchase intentions. Additionally, website quality was found to have a greater influence on perceived product quality when consumers had higher information asymmetries. Likewise, signal credibility was found to strengthen the relationship between website quality and product quality perceptions for a high quality website. Implications for future research and website design are examined.

http://ftp.misq.org/skin/frontend/default/misq/pdf/appendices/2011/WellsValacichHessAppendices.pdf

What signal are you sending? how website quality influences perceptions of product quality and purchase intentions

Recent trust research in the information systems (IS) field has described trust as a primary predictor of technology usage and a fundamental construct for understanding user perceptions of technology. Initial trust formation is particularly relevant in an IS context, as users must overcome perceptions of risk and uncertainty before using a novel technology. With initial trust in a more complex, organizational information system, there are a number of external determinants, trusting bases, that may explain trust formation and provide organizations with the needed levers to form or change individuals' initial trust in technology. In this study, a research model of initial trust formation is developed and includes trusting bases, trusting beliefs, trusting attitude and subjective norm, and trusting intentions. Eight trusting base factors are assessed including personality, cognitive, calculative, and both technology and organizational factors of the institutional base. The model is empirically tested with 443 subjects in the context of initial trust in a national identity system (NID). The proposed model was supported and the results indicate that subjective norm and the cognitive-reputation, calculative, and organizational situational normality base factors significantly influence initial trusting beliefs and other downstream trust constructs. Factors from some of the more commonly investigated bases, personality and technology institutional, did not significantly affect trusting beliefs. The findings have strategic implications for agencies implementing e-government systems and organizational information systems in general.

/pdf/why-do-we-trust-new-technology-a-study-of-initial-trust-1303i4fkco.pdf

Why do we trust new technology? A study of initial trust formation with organizational information systems

Designing Interfaces with Social Presence: Using Vividness and Extraversion to Create Social Recommendation Agents*

A reliability generalization study (a meta-analysis of reliability coefficients) was conducted on three widely studied information systems constructs from the technology acceptance model (TAM): perceived ease of use, perceived usefulness, and behavioral intentions. This form of meta-analysis summarizes the reliability coefficients of the scores on a specified scale across studies and identifies the study characteristics that influence the reliability of these scores. Reliability is a critical issue in conducting empirical research as the reliability of the scores on well-established scales can vary with study characteristics, attenuating effect sizes. In conducting this study, an extensive literature search was conducted, with 380 articles reviewed and coded to perform reliability generalization. Study characteristics, including technology, sample, and measurement characteristics, for these articles were recorded along with effect size data for the relationships among these variables. After controlling for number of items, sample size, and sampling error, differences in reliability coefficients were found with several study characteristics for the three technology acceptance constructs. The reliability coefficients of PEOU and PU were lower in hedonic contexts than in utilitarian contexts, and were higher when the originally validated scales were used as compared to when other items were substituted. Only 27 percent of the studies that provided the measurement items used the original PEOU items, while 39 percent used the original PU items. Scales that were administered in English had higher reliability coefficients for PU and BI, with a marginal effect for PEOU. Reliability differences were also found for other study characteristics, including reliability type, subject experience, and gender composition. While average reliability coefficients were high, the results show that, on average, relationships among these constructs are attenuated by 12 percent with maximum attenuation in the range of 35 to 43 percent. Implications for technology acceptance research are discussed and suggestions for addressing variation in reliability coefficients across studies are provided.

http://www.misq.org/skin/frontend/default/misq/pdf/appendices/2014/V38I1Appendices/HessMcNabBasogluAppendices.pdf

Traci J. Hess

Papers

What signal are you sending? how website quality influences perceptions of product quality and purchase intentions

Why do we trust new technology? A study of initial trust formation with organizational information systems

Designing Interfaces with Social Presence: Using Vividness and Extraversion to Create Social Recommendation Agents*

Reliability generalization of perceived ease of use, perceived usefulness, and behavioral intentions

Reliability Generalization of Perceived Ease of Use, Perceived Usefulness and Behavioral Intentions.