Information overload is one of the major problems for individuals and organizations in modern urban environments. This phenomenon has been studied for many years, and has proven to be more complex than researchers believed it to be. It is important to better understand this “pathology of information” for two reasons. First, it has a deleterious impact on work productivity and quality. Second, it has traditionally been a driver of Information Technology developments aimed at helping individuals to better cope with it. The study presented here aims at shedding light on the complexity of information overload, by examining the relationship between perceived information overload intensity and three traditional information overload predictors as well as one nontraditional predictor. The nontraditional predictor is power distance, or the extent to which less powerful members of a national culture accept that power is distributed unequally. Power distance was manipulated through the collection of data from 184 local managers and professionals (in New Zealand, Spain and the U.S.A.). The data analyses led to one surprising conclusion: perceived information overload intensity seems to be more strongly related to power distance than to the volume of written information or number of information transactions processed by an individual.
TopIntroduction
Typically information overload has been viewed as problematic and as leading to losses in work productivity and quality of work outcomes. Information overload has also traditionally been a driver of information technology developments; information technology solutions have often been developed specifically to help individuals cope with information overload (Turetken & Sharda, 2004). As early as 1970, the award winning writer and futurist Alvin Toffler argued that information overload would become one of the main problems facing modern society and organizations (Toffler, 1970). The emergence of the Internet and its increasing use by individuals and organizations (Chung & Tan, 2004; Teo, 2007) has been presented as contributing to increasing levels of information overload (Kiley, 1995; Berghel, 1997), apparently lending support to Toffler’s (1970) prediction.
Generally speaking, information overload can be defined as a state in which the amount of information an individual must process exceeds the individual’s information processing resources (O'Reilly, 1980).
The study presented here aims at shedding light on the complexity of the information overload phenomenon, by looking at it from a different and arguably novel lens. The study examined the relationship between perceived information overload intensity and one nontraditional and three traditional information overload predictors. One of the goals of the study was to compare the influence, if any, of the nontraditional predictor against the more traditional ones.
Power distance was the nontraditional predictor. Power distance is part of Geert Hofstede’s model of cultural dimensions (Hofstede, 2001; Lippert & Volkmar, 2007), and is defined as the extent to which less (and more) powerful members of organizations (e.g., employees and their supervisors) accept that power is distributed unequally. Hofstede's model has been widely applied in various disciplines (Sivakumar & Nakata, 2001), particularly in psychology, sociology, marketing, and management (Søndergaard, 1994). Hofstede’s model is considered by many to be the most comprehensive model of the influence of national culture on organizational behavior.
The traditional information overload predictors were the volume of written information processed by individuals, in terms of pages read and written on a daily basis; the number of information transactions, or the average number of information giving and information receiving interactions per working day; and business process knowledge, assessed as the number of months of formal education and hands-on practice needed to perform work-related activities well.
This is a cross-cultural research study (Hunter, 2006) in which variations in the power distance predictor were incorporated into the study’s design through the collection of data from three different countries, which also differ significantly in terms power distance. Data were obtained from 184 local managers and professionals in New Zealand, Spain and the U.S.A. The data were analyzed employing partial least squares-based structural equation modeling. The analysis led to one surprising conclusion, which is that perceived information overload intensity is more strongly related to power distance than to the volume of written information or the number of information transactions processed by an individual. This surprising conclusion is referred to here as the information overload paradox.