The main purpose of this study is to analyse the degree to which different management styles influence the quality of organisational communication in the UK’s restaurant industry. This chapter discusses and develops the research methodology of the underlying study, including the research philosophy, research approach, research strategy, population and sampling, methods of data collection, ethical considerations, as well as research limitations.
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This study employs a positivist research philosophy in its attempt to analyse the degree to which different management styles influence the quality of organisational communication in the UK’s restaurant industry. The basic premise of this philosophy is that the main purpose of the research is a scientific explanation. Hence positivists view social science as an organised method for combining deductive logic with accurate empirical observations of individual behaviour with the view to discovering and confirming a set of probabilistic causal laws that can then be applied to predict general patterns of human behaviour (Neumann 2003). The knowledge that develops through a positivist lens is grounded on meticulous observation and measurement of the objective reality that exists “out there” in the world, hence the need for the researcher to develop valid numeric measures of observations for use in studying the phenomena or variables of interest (Bryman 2008). In this study, the positivist philosophy allows the researcher to (1) collect specific data on different management styles and organisational communication, (2) develop a set of hypotheses and operationalise them based on important variables, and (3) empirically test the hypotheses with the view to corroborating existing relationships between different management styles and quality of organisational communication.
This study adopts a quantitative research approach, which is usually associated with a positivism research philosophy and a survey method of data collection (Weaver & Olson 2006). Yilmaz (2013, p. 312) defines the quantitative research approach “as a type of empirical research into a social phenomenon or human problem, testing a theory consisting of variables which are measured with numbers and analysed with statistics in order to determine if the theory explains or predicts phenomena of interest.” Available literature demonstrates that quantitative research is an approach for testing objective theories by examining the relationships between important variables of the study, which can be measured using instruments and analysed using statistical procedures; however, the variables must be evaluated using rigid rules of logic and measurement, truth, absolute principles and prediction in line with the positivism philosophy (Lee & Hubona 2009). Creswell (2014, p. 4) argues that the final written report of quantitative research “has a set structure consisting of introduction, literature and theory, methods, results, and discussion.” The main justification of using the quantitative research design in this study is that it allows the researcher to effectively test the stated hypotheses and respond to the underlying research questions by investigating the relationship between variables of interest to the study (Creswell 2009).
This study utilises a cross-sectional (survey) research design, as study participants are contacted at a fixed point in time to collect pertinent information on the attributes of interest using a standardised survey questionnaire (Balnaves & Caputi 2001). Available literature demonstrates that survey research avails “a quantitative or numeric description of trends, attitudes, or opinions of a population by studying a sample of that population” (Creswell 2014, p. 13). Consequently, a cross-sectional research strategy not only enables the researcher to study the attitudes and opinions of players in UK’s restaurant industry at a particular point of time but also examine associations between different management styles and quality of organisational communication by studying a sample of employees and managers working in the industry. Other justifications for using a cross-sectional research strategy include ease of application and capacity to be descriptive. However, the design has received criticism for selection bias, lack of clarity in demonstrating temporal bias, and incapacity to show causality (Balnaves & Caputi 2001).
Population & Sampling
The term “population” has been defined in the literature as a group of individuals or things of interest under exploration or examination by the researcher with the view to providing responses to the key research questions (Creswell 2014). In the current study, the target population include senior managers and employees working in the UK’s restaurant industry. Initially, a random sampling technique is used to select 8 hotels, restaurants and other hospitality institutions from an online database to serve as a foundation for the selection of managers and employees from these institutions. Owing to the nature of the information needed for the successful completion of the study, nonprobability sampling techniques are used in the development of the required sample. Specifically, the purposive sampling technique is used to select 10 senior managers from each institution, while a convenience sampling technique is used to select 10 employees from each institution. This means that the total sample for the present study is 160, or 80 senior managers and 80 employees.
It is important to note that sampling for the study has been done online through the assistance of human resource managers or corporate managers of the selected institutions. The suitability of purposive sampling technique in the selection of senior managers is grounded on the fact that it allows the researcher to gain an in-depth and holistic understanding of all the variables of interest to the study, as a purposive sample is selected or “handpicked” based on the participant’s expansive knowledge of all the issues that are of primary importance to the researcher (Sekaran 2006; Vogt 2007). Consequently, this sample has been critical in enabling the researcher to gain an in-depth and holistic understanding of the degree to which different management styles influence the quality of organisational communication in the UK’s restaurant industry. Convenience sampling is not only easier to administer, but it costs less than other sampling techniques in terms of resources and assists the researcher in the collection of pertinent information that would not have been possible using probability sampling techniques (Vogt 2007).
Methods of Data Collection
The present study draws on quantitative data collected by means of standardised questionnaire instruments administered to senior managers and employees in the UK’s restaurant industry. Questionnaires are described in the literature as “fixed sets of questions that can be administered by paper and pencil, as a Web form, or by an interviewer who follows a strict script” (Harrell & Bradley 2009, p. 6). In this study, standardised self-completed questionnaires are sent to participants using online protocols for completion and onward submission to the researcher, implying that participants are provided with adequate time to respond to the items contained in the questionnaires without the assistance of an agent (Potter 2003).
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One questionnaire set is used for senior managers and employees to facilitate the comparison of how each group perceives the association between different management styles and quality of organisational communication as necessitated by the cross-sectional research design. The self-completed questionnaire set is divided into two sections: the first section is concerned with collecting participants’ demographic information (e.g., position in the restaurant industry, age, gender, nationality, educational status and tenure of employment), while the second section requests participants to identify their level of agreement with a number of statements presented in the questionnaire using a five-point Lickert-type scale (“1=strongly disagree”; “2=disagree”; “3=neither agree nor disagree”; “4=agree”; “5=strongly agree”). The use of the Lickert-type scale is consistent with the quantitative research approach that “requires the reduction of phenomena to numerical values in order to carry out statistical analysis” (Gelo, Braakmann, & Benetka 2008, p. 268). Consequently, in the present study, the use of a Lickert-type scale allows participants being surveyed to quantify their preferences and thoughts on how different management styles influence the quality of organisational communication, hence the justification (Fowler 2008).
Drawing from Sekaran (2006), the following issues have been put into consideration during the questionnaire designing phase: (1) the wording of the questions, (2) the layout and appearance of the questionnaire, and (3) how categorising, scaling, and coding of variables will be done upon receipt of the questionnaires from the field. Web-based self-administered questionnaires have unique advantages over other data collection techniques such as structured and unstructured interviews, with available methodology scholarship demonstrating that they are less expensive due to low administration costs, have a greater geographical reach, and provide greater anonymity for participants due to the absence of the interviewer. However, they are criticised due to low response rates, incapacity to capture complex and ambiguous questions due to the absence of the researcher, and lack of opportunity to probe participants further owing to the fact that most items are closed-ended (Potter 2003; Harrell & Bradley 2009; Marsden & Wright 2010).
Validity & Reliability
Validity and reliability determine the accuracy of collecting data in research. Reliability estimates the consistency of the measurement used by the researcher in data collection, or more simply the degree to which a test or procedure produces similar results under constant conditions on all occasions; on the contrary, validity implies the degree to which the measure is effective in measuring what it is supposed to, or more precisely the extent to which a measure accurately represents the concept it claims to measure (Bryman & Bell 2008; Punch 2009).
In this study, reliability (e.g., consistency of results among participants, consistency of results across uses) is achieved through (1) standardising the questionnaire instrument, (2) documenting shifts or progress regularly, and (3) ensuring the stability of the different measures used in the data collection instrument (Bryman 2008; Bryman & Bell 2008). Validity (e.g., establishing relationships between different study variables, generalising the results to other study findings) is achieved through (1) ensuring the relevance and representativeness of questions in the standardised questionnaire by conducting a pilot study with individuals who are similar to the intended study participants (2) comparing the questionnaire to other similar validated measures of management styles and organisational communication patterns, and (3) establishing the correct operational measures for the theoretical concepts under investigation through effectively linking the questionnaire items and measures to the study’s research questions and hypotheses (Bryman & Bell 2008; Punch 2009).
Ethical considerations form an important constituent of any research process, with available literature demonstrating that ethical issues arise as the researcher is expected to “ensure that no harm occurs to [the] voluntary participants and that all participants have made the decision to assist after receiving full information as to what is required and what, if any, potential consequences may arise from such participation” (Polonsky & Waller 2010, p. 69). In the present study, the researcher has (1) sought for written permission from the senior management of the hotels, restaurants, and other hospitality institutions earmarked to participate in data collection, (2) ensured that any participation in the research process is voluntary and that all participants have been provided with the adequate information to make informed choices without coercion or deception, (3) ensured participants fully understand what they are being asked to do and are fully informed of any potentially negative ramifications related to such participation, (4) guaranteed individual confidentiality and anonymity of participants, and (5) facilitated the debriefing of participants and sharing with them the major findings of the study using online protocols (Gregory 2003; Polonsky & Waller 2010).
In the present study, dully filled questionnaires are cleaned, coded, and entered into the Statistical Package for Social Sciences (SPSS) version 18.0 for analysis. In line with the quantitative research tradition, the software is used to not only analyse data using descriptive statistics and inferential statistics, but also to present the findings using various formats, such as descriptive tables, cross-tabulations, bar graphs, and pie charts. It is important to underscore the fact that descriptive statistics are used in this study to describe the basic features and characteristics of the data received from the sampled senior managers and employees, hence providing simple summaries about the sample and the measures (Connolly 2007).
Consequently, univariate analyses of the data have been done with the view to developing frequency distributions of the various attributes of interest as well as measures of central tendency (e.g., mean, median, and mode) and dispersion (e.g., standard deviation and variance). The advantages of using descriptive statistics include (1) capacity to collect, organise, and compare huge quantities of discreet categorical and continuous non-discrete (numerically infinite) data in a more manageable form, (2) capacity to be employed in systematic observations of central tendency with the view to describing subject data information in a way that is less subjectively evaluated by others, and (3) capacity to identify with ease discreet or finite categorical variables such as participant’s sex, age in completed years, and employment status (Connolly 2007; Treiman 2008).
Inferential statistics, on the other hand, are used in the present study not only to demonstrate the association between the variables of interest (correlation) but also to make informed judgements of the probability that an observed variation between a response provided by senior management and employees is a dependable one or one that might have occurred by chance (Treiman 2008). More broadly, inferential statistics have been used in this study to (1) make inferences from the analysed data to more general conditions concerning the degree to which different management styles influence the quality of organisational communication in the UK’s restaurant industry, (2) make predictions on how different management styles influence the quality of organisational communication depending on the collected data, and (3) investigate the differences in responses between senior managers and employees in the UK’s restaurant industry (Connolly 2007).
The analysis of variance (ANOVA) and correlation (p) is used to analyse the degree to which different management styles influence the quality of organisational communication in the UK’s restaurant industry. ANOVA allows comparison of two or more populations (senior managers and employees) when interval variables are used by comparing the dispersion of samples with the view to making inferences about their means, while correlation (p) is employed to measure the similarity in the shifts of values of interval variables owing to the fact it is not influenced by the units of measure (Asadoorian & Kantarelis 2005). Overall, the two data analysis techniques (1) provide more comprehensive information than descriptive statistics, (2) yield important insights into relationships between variables, (3) reveal causes and effects and make predictions, (4) generate convincing support for a given theory, and (5) are generally accepted due to widespread use in business and academia (Runyon 2010).
It is evident that the low response rate experienced in the data collection phase has affected the generalisability of the findings in light of the fact that quantitative research should employ a large and representative sample (Sekaran 2006; Creswell 2014). The researcher has also been constrained by the limited time allowed for the completion of the research study and hence has been unable to substitute the selected participants who failed to submit their duly-filled questionnaires in time. Sufficient time could have guaranteed the engagement of a larger sample than has been used in this study, hence ensuring that the study findings are readily generalised to the larger population in the UK’s restaurant industry.
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