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Overall quantitative research aims to observe certain fundamental principles of logic and scientific frame of reasoning. There continues to be challenges on how quantitative research is conducted in the field of information systems.

Structured equation modelling (SEM) research identifies concerns about the standard of scientific enquiry method, the issue of the misconception of sustaining the consequent and the issue of collective validity. Therefore, rigor and robustness in instrument validity, constructs validity and path analysis validity maybe better achieved by attending to these three concerns. Measuring a multiple mediator construct in a hypothetical model continues to be a challenge for researchers in information systems research and related fields.

This paper aims to provide a thoughtful assessment of the contemporary issues of structural equation modelling methodology (SEMM), by providing rigid and robust SEMM that has several stages in specifying valid multiple mediators construct and the process to measuring in a path analysis model. This paper attempts to develop each stage of the methodology using relevant research to construct a methodology specified to test effects in multiple mediators in SEM using AMOS software. The methodology developed contains the two main phases; first is prior to data collection phase and the second phase is after the data collection, the use of this methodology design, for implementation, intended to support high methodological standards and subsequent quality in MIS research findings.

The research paper provides SEMM that has several stages in specifying valid multiple mediators construct and the process to measuring in a path analysis model.

The use of covariance structure modeling is explored as a means of moving toward a resolution of the debate over the antecedents of executive compensation. The major strength of this methodology is that it enables researchers to measure the effects of unobserved factors on measured variables. It is suggested that covariance structure modeling is a promising way of studying the effect of institutional isomorphism on executive compensation. The popular business press has questioned repeatedly the justification for and the performance effects of prevailing executive compensation systems (Crystal, 1988; Loomis, 1982; Patton, 1985). These articles argue that executives are more interested in creating wealth for themselves than for stockholders. They also underscore the absence of an obvious link between executive compensation and firm performance. Recent academic research on executive compensation adopts an agency perspective that emphasizes potential conflicts of interest between managers and stockholders. It contends that, in the absence of effective disciplining and monitoring systems, executive compensation plans may direct managers' efforts toward personal wealth enhancement to the detriment of firm value (Baumol, 1958; Berle & Means, 1932). In response, scholars have urged that executive compensation plans contain monetary incentives that only accrue to executives when shareholder wealth is maximized (Kerr, 1985; Rappaport, 1983; Tehranian & Waegelein, 1985). However, designing compensation systems that effectively align the interests of managers and stockholders requires a knowledge of the role and effect of relevant driving forces on compensation. Statistical research on executive compensation has been guided predominantly by a search for tangible, observable determinants (Ciscel & Carroll, 1980), examples of which have been firm size or growth rate (Baumol, 1967; Marris, 1963), inter‐firm and inter‐in‐dustry differences (Coughlan & Schmidt, 1985), and performance (Murphy, 1986). The emphasis on such tangible explanations is not surprising given the overwhelming use of econometric techniques, such as ordinary least squares regression (Ciscel & Carroll, 1980; Finkelstein & Hambrick, 1988), logistic regression (Walking & Long, 1984), time series analysis (Murphy, 1985), and event studies (Brickley, Bhagat & Lease, 1985; Coughlan & Schmidt, 1985; Tehranian & Waegelein, 1985). This paper argues that the focus on tangible, observable variables by compensation researchers is a methodologically ‐ driven practice that constrains theory building and testing. As a result, we may have ignored interesting and relevant theoretical frameworks for the study of executive compensation. We also have overlooked the use of analytical techniques that allow us to examine the role of potentially relevant latent constructs. In this paper, we will describe and illustrate the use of covariance structure modeling for the study of institutional pressures on executive compensation.

Recent literature has highlighted the importance of human resource management, knowledge management, and technical innovation as key elements for achieving competitive advantage. Furthermore, research has shown a positive relationship between these three variables. However, empirical research on this issue is still scarce. This paper analyzes those linkages using structural equation modeling with data collected from 373 Spanish firms. The findings show that there is a relationship among the variables, although it is more complex than described in previous studies.

Whether older or younger entrepreneurs may be better positioned to achieve performance outcomes for their ventures is a much debated question. Here, we draw on Galenson℉s theory of creativity to propose a contingency perspective for understanding the relationship between entrepreneur age and venture performance, suggesting that a venture℉s level of innovativeness plays a moderating role. Results from a representative sample of 1,182 nascent entrepreneurs revealed mixed support for our hypotheses. While a negative relationship was found between entrepreneur age and performance for those developing “innovative” ventures, no relationship was found between entrepreneur age and performance for those developing “imitative” ventures.

It is all too easy in the hectic world of business to get too involved with the day‐to‐day managing of processes and events. When this happens it is difficult to see the wood for the trees and the automatic pilot syndrome takes over. This does not suggest that you do not know what you are doing ‐ on the contrary you are probably as switched on to whatever activity you are managing as anyone could be. What you could be missing, however, is the explanation as to why you are doing it. If this sounds familiar to you, what might be needed is a detached period from your work. By this I mean stay on the high ground for a while so you can get an overview of what you are doing and, more importantly, why you are doing it. How many managers, I wonder, get the opportunity to question what they are doing? If you allow yourself to slip into complacency then you and your organization will soon lose competitive advantage.