Q1    What are the physical working conditions that contribute to increasing productivity of workers?

Q2    Research design includes incremental changes to supposed key variables; continual comparisons against predicted variable; and continuous observation.

Q3    The selection of workers is not random; there is no parallel control group; open observation takes place throughout, including interaction with the subjects.

Q1    From the list of general factors, is there a best combination? You would need to include cost in the equation – the best design might also be impossibly expensive.

Q2    You would have to start with any constraints on design and layout that are imposed by the proposed building itself. Then it makes sense to prioritize factors, perhaps on the basis of impact or cost. You might consider a sequence of studies which varies one factor at a time, in order to identify whether there is an optimal combination of design features. Some factors (such as density and layout) would be the same for everyone taking part in a particular study, while you could vary the ergonomics of the workstation for different workers within the same study.

Take solution from source: Activity 22: Knowing about Probability – Catherine Dawson’s 100 Activities for Teaching Research Methods.

Group – Discuss the reasons underlying the decisions to adopt a sampling strategy based on a) quota sampling, b) snowball sampling and c) purposive sampling. How do the authors of the studies you selected justify their choice?

Quota sampling is a type of non-probability sampling technique that allows researchers to target individuals they wish to sample based on certain known criteria or characteristics such as gender or educational level. The population is divided into groups (also called strata) and samples are taken from each group to meet a quota. This can ensure a proportionate representation of particular strata (groups) and facilitates comparisons between groups. Quota sampling is inexpensive, fast and easy to carry out and it tends to be used when probability sampling techniques are not a viable option. A major problem with quota sampling is the introduction of unknown sampling biases.

Snowball sampling is another type of non-probability sampling technique. It involves research participants recruiting other participants and is often use when potential participants are hard to find, for example when one seeks to sample concealed populations, or when higher levels of trust are required to initiate contact. It is called snowball sampling because once ‘you have the ball rolling’ (participants start recommending/recruiting other participants) your ball (i.e. project) will pick up more ‘snow’ and become larger and larger.

A purposive sample is a non-probability sample. The main goal of purposive sampling is to focus on particular characteristics of a population according to the needs of research question and emerging theory. For example, a researcher may look for critical cases, for maximum variation or for a very homogenous sample. Such sample is not representative of the population, but this may not be considered a weakness when conducting qualitative research. Researchers rely on their judgment when choosing research participants. Usually, the sample being investigated is quite small.

Q1The study involved gathering data from multiple sources over a period of time, and this was appropriate to studying the complex inter-relationships and processes within the company. But also the feedback to key actors in the company also added to the validity of the conclusions we drew.

Q2   Because this is a unique study, the findings can only be generalized theoretically. That is, the case study needs to be able to demonstrate something about dynamic capabilities, knowledge management, or the relationship between the two of them, which supports, contradicts, challenges or adds to current theories in the literature.

Q3   They do make sense if you want to publish the results of the study in an academic journal. However, there are plenty of stories that came out of the study which can provide useful anecdotes to illustrate decision-making processes, group dynamics and so on – which we had not expected in the first place, but which made good stories in their own right.

Q1   This depends on whose version of grounded theory Suzanne follows. She uses open coding, which leads to a central category (see Chapter 7), but there is no theoretical sampling, nor saturation. The interplay between external theory/literature and data is more complex than as outlined in Glaser and Strauss.

Q2   We think this deviation is quite appropriate, provided Suzanne is able to articulate what and why. Reasons include the constraints of the research setting/access, the nature of the theory she is looking at, and the conscious combination of theory development and deduction.

Group – Consider the case of researchers conducting applied research or evaluation research. In order for them to use the template, would you add or omit any questions? If yes, which ones? Can you explain why?

Broadly, where the template presented is as useful for applied research and evaluation research as it is for basic research. However there are some differences in relation to emphasis and the relevance of some of the questions. Background, rationale and aims are clearly still very important although the objectives and deliverables and the value of the research to an organisation come to the fore in applied and evaluation research. Also important is the setting or context in which the research takes place but here, it is because applied research and evaluation research places emphasis on practical outcomes and therefore relevance becomes closely related to particular contexts and these need to be additionally recognised. Many process consultants are keen to understand in detail the cultural historical context in which the research or evaluation is to take place so that the findings they present to clients have the best chance of gaining acceptance.

In terms of data, applied or evaluation research needs to take into account just how the evaluation (of success) will take place. For example what measures or surrogates or benchmarks will be used? This gives rise to the possibility that measurement might be so important in the context of the data question that it requires a separate category of its own.

In terms of sampling two additional considerations might well be cost and time. Although in basic research time is never limitless in applied and evaluation research the constraints are often that much greater.

Access, might be easier to gain for applied and evaluation research as the research it is likely to have been commissioned. As a consequence the organisation has already demonstrated a commitment to engage.

Ethics applies in the same way to any research and ethical standards need to be viewed as a given.

Unit of analysis – here research designs might differ to the extent that applied and evaluation research needs to ensure it focuses on the utility that it offers. The processes and practicalities will very much depend on the type of research that is to be conducted whatever type of research is taking place. This said a feature of process consultancy (a popular type of applied research) and evaluation research often require longitudinal studies to take place. This requires a commitment to collect information regularly over time and therefore for the relationship to remain strong between the researcher and the organisation over time.

Finally, in relation to theory, consultants are keen to understand not simply ‘expoused theory’ but also ‘theories in use’. The latter includes practitioner knowledge (knowing) that is enacted and forms practice. This presents a challenge for researchers and requires particular skills. This often involves understanding managers’ implicit as well is explicit understandings, and how these were formed in order that they might be changed.