Millions of employees now use portable electronic tools to d o theirjobs from a "virtual office" with extensive flexibility in the timing and location of work. However, little scholarly research exists about the effects of this burgeoning work form. This study of IBM employees explored influences of the virtual office on aspects of work and worwlife balance as reported by virtual office teleworkers (n = 157) and a n equivalent group of traditional office workers (n = 89). Qualitative analyses revealed the perception of greater productivity, higher morale, increased flexibility and longer work hours due to telework, as well as an equivocal influence on work/life balance and a negative influence on teamwork. Using a quasi-experimental design, quantitative multivariate analyses supported the qualitative findings related to productivity, flexibility and worWlife balance. However, multivariate analyses failed to support the qualitative findings for morale, teamwork and work hours. This study highlights the need for a multi-method approach, including both qualitative and quantitative elements, when studying telework.
IntroductionThe rich legacy of qualitative research has yielded a wide variety of approaches and methods (grounded theory, ethnography, action research, focus groups, interviews, case studies, etc.). This chapter will summarize specific steps from the traditions of grounded theory, ethnography, and other schools of thought that have emerged from the fields of sociology, anthropology, and psychology. Our specific focus will be on the methods we believe are most useful and frequently used in organizations. These methods can be combined to create an approach tailored to the research question and situation. In fact, triangulation of results from multiple approaches can yield more reliable and valid conclusions (Tucker, Powell, and Meyer, 1995) and is particularly important when results will be used for decisions that may have significant risk attached (e.g., attraction and retention strategies, implementation of a new performance appraisal system). Because systematic approaches can enhance the reliability and validity of conclusions drawn from qualitative research, we hope to strike a balance between standardization and the flexibility that has been the hallmark of many qualitative researchers and theorists (e.g., Glaser and Strauss, 1967).In this chapter, guidelines for choosing when qualitative research may be most appropriate and recommendations for how to collect and analyze qualitative research in organizations will be provided. Our purpose is not to provide an exhaustive description of different qualitative research approaches, because there are already several definitive sources for each technique. We direct the reader to Lee (1999) or Symon and Cassell (1998) for overviews of organizational applications of multiple methods, to Creswell (1998) or Maxwell (1996 for a more general review of qualitative research, and to Miles and Huberman (1994) for data analysis techniques. While we will be faithful to these original sources, which are often oriented to the academic researcher, we will also 162 Bachiochi, Weiner provide a perspective intended for the organizational researcher. Thus, unique situations and constraints on research in organizations will be covered as the specific steps and techniques are summarized. To facilitate this process, the topic of employee retention and attrition will provide a running context for our recommendations.The different approaches available also involve varying levels of participant involvement, which can be a significant factor in selecting a method. In this chapter, the approaches will be discussed starting with the highest level of participant involvement. For instance, focus groups require active involvement of the participants in the data collection process. Observational studies may vary widely in the level of involvement and potentially the degree to which participants are aware of the research being conducted. Case studies, especially if they rely heavily on written or archival records, could require very little participant involvement. Finally, some of the overarching is...
In this response to Guzzo, Fink, King, Tonidandel, and Landis (2015), we suggest industrial–organizational (I-O) psychologists join business analysts, data scientists, statisticians, mathematicians, and economists in creating the vanguard of expertise as we acclimate to the reality of analytics in the world of big data. We enthusiastically accept their invitation to share our perspective that extends the discussion in three key areas of the focal article—that is, big data sources, logistic and analytic challenges, and data privacy and informed consent on a global scale. In the subsequent sections, we share our thoughts on these critical elements for advancing I-O psychology's role in leveraging and adding value from big data.
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