Research strategy

There are many types of research strategies that can be used in business and management research. Table 3-1 shows seven of these strategies suggested by Saunders et al. (2009) that are suitable for different research purposes and for answering different types of research questions. This research is an Explanatory research, which aims to explain the causal relationships among the study variables and to answer the following research question: What operational practices in the UK manufacturing companies can improve their financial performance?

Therefore, several alternatives from the highlighted strategies in table 3-1 could potentially be used in this study. However, by comparing some of the potential strategies, archival research was considered as the most suitable strategy for this study. In the following section, the reasons for using archival research and the reasons for not using the other potential strategies are explained.

Table 3-1 Potential research strategies

Research strategies Purpose of the research Research questions

Experiment Exploratory, Explanatory How? Why?

Survey Exploratory and_Descriptive Who? What? Where? How much?_{and how many?}

Case study Explanatory and_Exploratory

Why? What? How? (although survey strategy is more concerned with what and how)

Action research Finding a solution for

organisational issues How? Grounded theory Explanatory What? Why? Ethnography Descriptive and_Exploratory Why? Archival research Exploratory, Descriptive or

Explanatory

Who? What? Where? How much? and how many?

A.1.4 Experiment strategy

Experiment strategy is suitable for Explanatory research; however it is more suitable for answering ‘how’ and ‘why’ questions (Bordens & Abbott, 2011), rather than ‘what’ questions as in this study. Saunders et al. (2009) argues that because of the design needs of this strategy, the selected samples in these studies are non-representative which lead to problems of generalisability.

An example of experiment research is a study conducted by Banker et al. (2004). Using 480 M.B.A students, this study evaluates the influence of strategically linked measures in a Balanced Scorecard on individuals’ evaluation of performance of business unit managers. The study showed that when individuals are told about the strategy of a business unit, they rely more on strategically linked measures than non-linked measures (Banker et al., 2004). However, the authors pointed out the three main limitations of their study design which might have influenced their findings:

1- The participants did not have general business experience.

2- They did not have the same incentives as business managers have in real life. 3- The information about business strategy was directly provided to the participants.

The limitations in Banker et al. (2004) study show how similar limitations in the design of experiment strategy might influence their findings. Therefore, the experiment was not a suitable strategy for this study.

A.1.5 Survey

The survey strategy is suitable for answering the ‘what’ question; however there is a limit to the number of questions in a survey, and therefore the collected data is unlikely to be comprehensive (Kalof et al., 2008). Also, most of the earlier studies that had examined the relationship between companies’ operational practice and financial performance used survey strategies to collect their data. Many of those studies such as Wang et al. (2014) and Dubey & Gunasekaran (2015) stated that their findings are based on subjective data, and may not reflect the actual performance of companies. To overcome this limitation, Nilsson et al. (2001) suggest using archival data to complement the findings based on perceptual data.

Similarly, using a single respondent or a single method of data collection for both operational and financial variables can lead to finding a false covariance between the variables (Podsakoff et al., 2003). To overcome this limitation, authors such as Sila (2007) and Li et al. (2010) suggest using multiple respondents (Sila, 2007) or multiple sources (Li et al., 2010) for data collection. Therefore, to avoid repeating the limitations of the earlier studies, a survey strategy was also not selected in this study.

A.1.6 Case study

Case study strategy is suitable for an Explanatory research and is also suitable for answering ‘what’ questions (Jonker & Pennink, 2010). However, there is a limitation in generalising the findings from a case study to a wider group of companies (Mitchell & Jolley, 2010). For example, Rucci et al. (1998) report findings of a case study research at a US department store (Sears, Roebuck and Company). The company managers decided to make the company ‘a compelling place to work, to shop, and to invest’. Over a course of eighteen months, the company collected data on many measures related to their customer satisfaction, employee satisfaction and financial performance. Using the causal pathway modelling method, the company developed a model which connects their employees’ satisfaction to customer satisfaction and profitability.

Although the developed model in Rucci et al.’s (1998) study is useful for their company, it cannot be generalised to other companies. The purpose of this study is to find a generic model that can be applied in majority of the UK manufacturing companies. To make a generic conclusion, there is the need to gather a larger number of case studies. Therefore, considering the limitations of time and other resources, it was not feasible to collect a large number of case studies in this research.

A.1.7 Grounded theory

Grounded theory is also an alternative for performing Explanatory research and for answering ‘what’ questions. However, Sreejesh & Mohapatra (2014) argue that this strategy is associated more with Inductive research. However, a large number of studies in the literature have explored the relationship between operational practices and financial performance. Therefore, Deductive research is more suitable for this study and so using a grounded theory is not relevant to this study.

A.1.8 Archival research

An archival research strategy is selected for this study. Based on Bordens & Abbott’s (2011) and Saunders et al.’s (2009) recommendations, the following describe the benefits of using the archival the research strategy for this study:

1- It is suitable for Explanatory research purposes and for answering ‘what’ questions: this study

uses an Explanatory research to find causal relationships between operational practices and financial performance in UK manufacturing companies. The research question of the study is: What operational practices in the UK manufacturing companies can improve their financial performance? Therefore, the archival research strategy is fitting for the purpose and the research question of this study.

2- It is less intrusive method of data collection:this strategy is a less intrusive method of data collection (Saunders et al., 2009). The companies’ information is collected from two independent data sources. Their operational data are collected from the IMechE’s archive of the companies who have entered the MX Awards between 2006 and 2011. The companies who have entered the MX Awards had the incentive of winning an award or to find the areas of improvement in their operational practices. Therefore, they were more likely to provide the information, than if they were supposed to provide that information to an academic researcher with no direct benefit for their business. For each of the companies that had entered the MX Awards, their financial data were collected from the financial analysis made easy (FAME) and Amadeus databases. Therefore, the advantage of this method is that collected data is less intrusive than if the information had been collected directly from the companies.

3- There are savings in time and financial resources: since the data is already collected, there is less

time needed for data collection, which results in great savings in time and financial resources (Saunders et al., 2009). Using archival data to collect companies’ operational and financial data was less time- consuming than if it had been collected via a survey. However, the format of the original data needed to be changed before it could be used for statistical analysis.

4- There is the potential for longitudinal analysis: archival research strategy allows the company to answer research questions which focus on the past and this provides the researcher with the potential for conducting a longitudinal analysis (Saunders et al., 2009). From the IMechE’s archival data, the companies’ operational practices were only available for the year in which they had entered the MX Awards. However, the financial ratios of those companies for the year of participation in the awards were collected and compared with their performance in the year before participation and three years after that. Therefore, it was possible to evaluate the impact of the companies’ operational practices on their financial performance up to three years after their participation in the MX Awards.

Despite the advantages of using archival data, mentioned above, Saunders et al. (2009) point out the following disadvantages of using this strategy in a research study.

1- Imprecise information: the archival documents may not contain the precise information needed to

answer the research questions, or the definition of the data may not be suitable for the study (Saunders et al., 2009). However, this problem is not applicable to this study as the data sources of the study contain relevant information that is suitable to answer the research question.

2- Problem with accessing the data and missing data:the researcher may be refused access to the data

because of confidentiality reasons, or there might be some missing data in the archives (Saunders et al., 2009). In this study, the copyright owners of the IMechE archive gave permission to the author to have access to their database, and the financial information of those companies was collected from publicly available databases (i.e. FAME and Amadeus). Therefore, there was no problem about accessing the data in this study. There was some missing data in the archival data of the study, but this did not affect the analysis as it was possible to reach statistically significant findings with the available data.

3- No control over data quality and presentation:there is no control over data quality in archival research and the original purpose of the data may have affected the data presentation (Saunders et al., 2009). As explained in section 3.3.1.2, the quality of the archival data is higher than if collected via a survey. However, presentation of the data was not suitable for analysis in their original format. As explained in section 3.4.2, before the data was analysed, some preliminary steps were needed to prepare the data for analysis.