Quantitative Research Design
BTM 7303, Assignment 8
DuBose, Justin Z.
Dr. Susan Petroshius
28 November 2017
Introduction to Study
This paper is a brief examination of e-leadership and the accompanying communication challenges that twenty-first century e-leaders will encounter. E-leadership is an academic field of study that has emerged since the turn of the millennium (Savolainen, 2014) and one which involves organizational leadership of highly technological structures stretched over different cultures and geographic regions (Avolio, 2014). Savolainen (2014) noted that as the presence and capability of technology increases throughout the workforce, it places new demands on e-leaders in the specific area of communication. Chua (2017) concluded that e-leaders face the unique communication challenge of bringing about change in individual performance and organizational culture by means of information and communication technology. These challenges will be elaborated on and discussed in greater detail in subsequent sections when dealing with the research problem and purpose.
The research problem being addressed in this study is this: is one mode of technological communication (electronic mail, telephonic conferencing, or video conferencing) employed by organizational e-leaders more effective than others in producing the desired action when it is received by team members dispersed over large geographic areas? Avolio (2014) stated that e-leadership encompasses organizational structures spread over large geographic regions, and this study takes the problem of organizational dispersion over such large geographic areas and examines the effectiveness of various modes of virtual communication in producing results and responses.
The problem of effective technological communication by e-leaders has been the subject of recent research and, in particular, the correlation of e-communication and the production of the desired response by recipients (Sarros, 2014; Lilian, 2014). Albidewi (2014) experimented with the expediency of action and policy implementation by traditional and technological means and concluded that technological communication excels in a faster implementation of actions and policies over traditional means. Additionally, in his recent study on e-leadership and communication, Sarros (2014) found that e-communication with direct language was more effective in achieving outcomes than either “meaning-making” or empathetic language. The problem of the effectiveness of a particular mode of communication over another in producing the desired action has not been examined in recent literature on the subject. However, Lilian (2014) noted that, while this problem has not been addressed directly in existing literature, there is a great and prevalent interest in exploring the impact of virtual communication by organizational e-leaders. This gap in existing literature highlights the need for the study to be conducted and forms the basis for this study on these aspects of communication in e-leadership.
The purpose of this study is to employ various modes of e-communication by the e-leader to team members within the organization and discover which mode is more effective in producing the desired action of the leader by those team members who receive the e-communication. This purpose will be achieved by noting the action intended by the e-leader and tracking the variety of responses by recipients of the communication and the frequency with which the desired action was or was not carried out by individual recipients. For the purposes of this study, the effectiveness of communication is measured by the action it produces by team members and the degree to which it aligns with the intent of the e-leader. Within subsequent sections about quantitative methodology and design, details regarding the measurement of these variables will be discussed.
In addressing this research problem, three research questions will be asked and analyzed throughout this study. Each research question addresses a mode of e-communication from the e-leader and its correlation to action by organizational team members. What is the correlation between desired action by the e-leader and production of action when communicated by electronic mail to organizational team members? What is the correlation between desired action by the e-leader and production of action when communicated by telephonic conferencing to organizational team members? What is the correlation between desired action by the e-leader and production of action when communicated by video conferencing to organizational team members?
In answering these research questions, certain hypotheses are posited as a means of guiding the research. Hoy (2010) defined a research hypothesis as “a conjectural statement that indicates the relationship between at least two variables”. The following hypotheses, then, indicate the expected conceptual relationships between the independent variable of e-leadership communication mode and the dependent variable of the team member response.
The expected relationship between these two variables is that the modes of communication with more subsequent layers of human interaction (video conferencing, for example) will produce an action closer to the desired response of the e-leader than modes of communication with less layers of human interaction (electronic mail, for example). This hypothesis is congruent with the research findings of Serban (2015) who experimented with face-to-face organizational teams and virtual teams and concluded that multiple points of human interaction in communication between leader and follower produce greater results than fewer points of human interaction in communication. Expected results with this hypothesis are that video conferencing produces the desired actions by team members to a greater degree than telephonic conferencing, and telephonic conferencing produces the desired actions by team members to a greater degree than electronic mail.
Use of Quantitative Methodology
In answering these research questions, a quantitative methodology will be utilized in this study. This quantitative methodology will explore the relationship between the independent variable of the mode of e-communication and the dependent variable of the behavior response by virtual team members. This quantitative methodology will track the correlation of communication to successful action by its recipients. In examining existing literature on the subject, quantitative data is frequently collected by surveys (Jiang, 2016); (Patchanee, 2011); (Verma, 2016) as well as by conducting research experiments (Brooks, 2010); (Serban, 2015); (Weng, 2014).
Surveys could be employed to answer the research questions in this study. One of the primary benefits of quantitative data collection by surveys is ease of widespread data collection. Verma (2016) conducted online surveys using the “Google Docs” platform. This quantitative instrument was chosen due to the benefit of expediency – results were tabulated instantly – and convenience – large numbers of surveys could be conducted by the researcher without having to travel to physically conduct the surveys. In the case of this research, surveys provide a viable option of quantitative data collection in that each question could be answered by both e-leaders and team members in the study.
Experiments could also be conducted to answer the research questions in the study, and provide additional benefits beyond surveys, though a disadvantage is that they require more work on the part of the researcher than surveys. Serban (2015) conducted an experiment with various groups and observed that experimentation allows the researcher to collect more data about subjects than responses to a survey, among such data are group dynamics, behavior, psychology, as well as responses to the independent variable. For the purposes of this study, experimentation will be conducted to determine what correlation exists, if any, between the mode of communication and team member response.
Quantitative Methodological Design
The quantitative methodological design of this study will be an experiment involving three separate teams (coded A, B, and C) of four members within the organization who receive communication from the organizational e-leader. Members of these teams will only be connected to the e-leader through virtual means and will receive all communication virtually.
This experiment will utilize the three modes of communication (electronic mail, telephonic conferencing, and video conferencing) to communicate instruction from e-leader to virtual team members. These modes of communication will be coded numerically as 1 (electronic mail), 2 (telephonic conferencing), and 3 (video conferencing). Three desired outcomes will be determined by the e-leader and communicated to virtual teams A, B, and C using methods 1, 2, and 3. The desired outcomes will be communicated using three different modes to three different teams (coded as outcome A1, B1, C1, A2, B2, C2, A3, B3, and C3).
The frequency of desired successful outcomes by virtual team members will be measured and correlated to individual modes of communication. For example, one of the desired outcomes will be for team members to develop and present a plan of action for integrating new team members. Each team will present their plan to the leader, who will, with the researcher, determine the degree to which each team successfully accomplished the intended objective. Each of these interactions between researcher and e-leader will be aimed at discovering which communication method more frequently and successfully achieved the desired results.
One of the most important elements in any study is the process by which data will be analyzed. In the case of this qualitative study, data will be examined by both team and communication mode. Was there a correlation between a particular mode of communication and the achieving of desired results? Was there a particular team that did a better job of accomplishing objectives across multiple communication modes? These questions will be answered by both the observations of the researcher and the conclusions of the e-leader.
Included within data analysis is the factoring in of Type I and Type II errors. A type I error is the likelihood of the researcher concluding that a difference exists between variables when it does not (Hoy, 2010) and a type II error is the likelihood of the researcher concluding that no difference exists between variables when it fact it does (Hoy, 2010).
To account for type I and type II errors, the largest sample size available will be selected as increasing sample size increases statistical power, thereby decreasing the likelihood of error in the research (Hoy, 2010). Following this rationale, surveys would provide the easiest access to a larger sample size, but the chosen methodology of experimentation, although providing more work for the researcher, allows for a greater breadth of data collection.
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Avolio, B., Sosik, J., Kahai, S., Baker, B. (2014). "E-leadership: Re-examining transformations in leadership source and transmission". The Leadership Quarterly, 25(1), 105-131. Retrieved November 29, 2017.
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NG, LR, NCU, USAR
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