by Necmi K Avkiran (Online CV)

Blackboard mySI-net Library Web Catalogue Preliminary Research Proposal Outline Starting and Finishing Your Research Degree UQ my.UQ UQ Business School  ABDC Journal  Rankings   Google Finance Google Scholar

This homepage is primarily dedicated to students and academic research.

Upcoming world finance conferences can be accessed here.

You can look up a Finance term by connecting to Campbell R Harvey's glossary or Investopedia. A more general glossary can be found at A site that explains finance concepts in some detail but in a jargon-free language is Financialized.

Visitors to this website are also encouraged to check out the Melbourne Mercer Global Pension Index which measures the adequacy, sustainability and integrity of a country's pension system.

Those interested in publishing in academic journals are invited to read 'Empowering Yourself to Publish in International Refereed Journals'. A sample cover letter to editor, reply to reviewers, and reply to a rejection can be accessed here.


If you are in the process of preparing an application to enrol in a Masters by research or a Ph.D. degree, please see the suggested Preliminary Research Proposal Outline BEFORE you send in your application. Make sure you also check your school's specific requirements.

If you are a postgraduate student starting a Masters or Ph.D. program, you may want to read Starting and Finishing Your Research Degree.

Ph.D. and Masters by research students should consult their principal supervisors for the preferred presentation style as well as the university's general guidelines. Postgraduate students should find out about their school's referencing guidelines before writing up their theses.

Here is another link you may find useful: 'Writing tips for PhD students'.


PLS-SEM is a non-parametric, multivariate approach based on iterative OLS regression designed to maximise explained variance in latent constructs (Lohmöller, 1989; Wold, 1982). Latent constructs are indirectly observed through a number of indicators. PLS-SEM is known to be an appropriate method when working with composite models of prediction in exploratory research; it is also robust with skewed data (Hair et al., 2012a; Henseler et al., 2014). The three main reasons for selecting the PLS-SEM approach are small sample size, presence of formative indicators, and non-normal data (see Table 1 in Hair et al., 2014). The reader is referred to Hair et al. (2017) for a detailed exposition of PLS-SEM. Two of the advantages of PLS-SEM over CB-SEM are (a) a focus on predicting dependent latent variables (Evermann and Tate, 2016; Shmueli et al., 2016), often a key objective in empirical studies, and (b) the ability to accommodate indicators with different scales. In addition to being robust with skewed data because PLS-SEM transforms non-normal data according to the central limit theorem, it is also considered an appropriate technique when working with small samples (Henseler et al., 2009; Hair et al., 2017).

A demonstration of PLS-SEM in SmartPLS software ( has been uploaded to

In Banking and Finance disciplines, a paper that explains step-by-step PLS-SEM analysis exists in Avkiran NK, Ringle CM, Low R (forthcoming) Monitoring transmission of systemic risk: Application of PLS-SEM in financial stress testing, The Journal of Risk

Handbook released by Springer called "Partial Least Squares Structural Equation Modeling: Recent Advances in Banking and Finance"

Lohmöller J (1989) Latent Variable Path Modelling with Partial Least Squares (Physica-Verlag, Heidelberg).
Wold H (1982) Soft Modeling: The Basic Design and Some Extensions, in: Jöreskog KG, Wold HOA (Eds.), Systems under indirect observations: Part II: 1-54.
Hair J, Sarstedt M, Pieper T, et al. (2012a) The use of partial least squares structural equation modeling in strategic management research: A review of past practices and recommendations for future applications. Long Range Planning 45: 320-340.
Henseler J, Dijkstra T, Sarstedt M, et al. (2014) Common beliefs and reality about partial least squares: Comments on Rönkkö & Evermann (2013), Organizational Research Methods 17: 182-209.
Hair J, Sarstedt M, Hopkins L, et al. (2014) Partial least squares structural equation modeling (PLS-SEM): An emerging tool in business research, European Business Review 26(2): 106-121.
Hair J, Hult G, Ringle C, et al. (2017) A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM), 2nd edition (Sage Publications, Thousand Oaks, California).
Evermann J and Tate M (2016) Assessing the predictive performance of structural equation model estimators. Journal of Business Research 69: 4565-4582.Shmueli G, Ray S, Velasquez Estrada J, et al. (2016) The elephant in the room: Evaluating the predictive performance of PLS models. Journal of Business Research 69: 4552-4564.
Henseler J, Ringle C and Sinkovics R (2009) The use of partial least squares path modeling in international marketing. New Challenges to International Marketing: Advances in International Marketing 20: 277-319.


This homepage also mirrors links to DEA. DEA is a non-parametric technique that allows measurement of relative efficiency of decision-making units (DMUs). DMUs can be banks, university departments, general practices, supermarkets, real estate agents, hotels and so on. DEA allows you to identify the potential improvements that can be made in each DMU, as well as identify those DMUs that can be regarded as benchmarks.

The third edition of the DEA book, Productivity Analysis in the Service Sector with Data Envelopment Analysis, has been available since early May 2006. Here you can read more about the book and download it. The book is no longer supported by the author(s)

You can also download data by clicking on the relevant links below. I have endeavoured to provide the data used in the chapters I have written. If the data you are looking for are not here, they are either already reproduced in the book or are in the care of the other contributors to the book (see footnotes to chapters for individuals' email addresses).

Chapter 2 - Chapter 3 - Chapter 4 - Chapter 5 - Chapter 6 Model 1 - Chapter 6 Model 2 - Chapter 6 Model 3 Win1 - Chapter 6 Model3Win2 - Chapter 6 Model3Win 3 - Chapter 6 Model3Win4 - Chapter 6 Model3Win5 - Chapter 6 Model3Win 6 - Chapter 9 Transport - Chapter 9 Pensions - Chapter 13 - Chapter 14

Any errors discovered after printing of the book will be posted here.

Data used in the paper published in the Journal of Banking and Finance [1999, 23(7), pp.991-1013] can be downloaded here; Australian Bank Data for 1995.

You can make a quick start to your DEA project by following this checklist.

An informative DEA site is maintained by Professor Ali Emrouznejad

Main commercial DEA software applications can be viewed here: DEAFrontier, DEA Solver Pro, Frontier Analyst, and PIM-DEAsoft. There are also free DEA software such as DEAP and DEAOS.

CEPA, Centre for Efficiency & Productivity Analysis, provides a portal for working papers, grants and expertise in this area.


My UniEvaluation is designed to bring flexibility to student decision-making in the form of ability to easily compare universities against each other on multiple criteria.

Reports generated rank universities on key performance indicators (KPIs) to be selected by students and pre-selected university resource variables. The relative performance analysis behind this website benchmarks a university against others in Australia by distinguishing those who are more successful in converting their given inputs (resource variables) to outputs (measures of outcomes desired by students or KPIs).

Blackboard mySI-net Library Web Catalogue Preliminary Research Proposal Outline Starting and Finishing Your Research Degree UQ my.UQ UQ Business School  ABDC Journal  Rankings  Google Finance  Google Scholar

This homepage is developed and maintained by

Necmi K Avkiran, PhD, F Fin, MASOR (Online CV)

The University of Queensland, UQ Business School

St Lucia Campus, Brisbane, Queensland 4072, Australia

email:     tel.+61 7 3346 3282    fax.+61 7 3346 8166

Established on 17 October 1997. 

I also would like you to meet my late cat Petrushka. She loved to sleep all day long and she was as affectionate as a puppy (Oct 1988 - 10 September 2004).  Back to top

Disclaimer: This web page is not officially approved by The University of Queensland. Any views expressed are that of Associate Professor Avkiran only.

Copyright 2018 by Necmi K Avkiran