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«DiscoVeriNg HomelessNess Volume 13, Number 1 • 2011 U.S. Department of Housing and Urban Development | Office of Policy Development and Research ...»

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A pilot study of the relationship that exists between organizational culture and the use of the information management software among homeless-services providers found that two characteristics of organizational culture—rigidity and proficiency—are positively related to individual staff members’ technology use (Cronley and Patterson, 2010). Organizational rigidity is defined as the degree to which organizations expect staff members to follow uniform policies and procedures for work practices; organizational proficiency is defined as the degree to which organizations emphasize competency, provide training and professional development opportunities for staff members, and expect them to provide the highest quality of services (Glisson et al., 2008). It is possible that staff members in organizations with clearly defined policies and procedures are more accustomed to learning new software that requires fairly systematic operation. Moreover, it is logical that in

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organizations that value staff competency, the culture better supports the use of new technologies than those that do not value competency as much.

Diffusion of Innovations and Organizational Change Everett Rogers (1962) developed the theory of diffusion of innovations (DOI) to explain how new ideas spread among people and social networks. Its central point is that any technology is embedded in a larger social system that influences its implementation. Diffusion is “the process by which an innovation is communicated through certain channels over time among members of a social system” (Rogers, 2003: 5), and innovation is “an idea, practice, or object that is perceived of as new by the individual or other unit of adoption” (Rogers, 2003: 11). Examples of DOI’s application in the social sciences include discussion of evidence-based practices (Carboneau, 2005; Herie and Martin, 2002), public health campaigns (Dearing, 2004; Haider and Kreps, 2004); and substanceabuse treatment (Oser and Rowman, 2007). Although useful as a starting point for understanding technology diffusion, DOI applies largely to individuals rather than to organizations or groups as the adopting unit, and it focuses more on the process of spreading ideas than on sustaining behavioral change. Because homeless-services providers are adopting HMIS, and because the goal is to implement and sustain the technology use, an improved model of DOI is necessary.

The theories of sociotechnical systems and organizational culture enhance the applicability of DOI to organizations. Although DOI was the first to identify the role of social systems in the spread of new ideas, sociotechnical theory (Trist and Bamforth, 1951) relates this concept to organizations and explains how new ideas may operate in this setting. At its most basic level, the sociotechnical system contains two components: the technical system and the social system (Rosseau, 1977). The organization consists of technical productions, including equipment and operations; the individuals who use and operate the technologies; and the work structure that coordinates interaction between workers and technologies, including the management and job responsibilities and allocations (Trist and Bamforth, 1951). Trist and Bamforth conceptualized organizations as “complex, dynamic structures in symbiotic relationships with their environments” (Trist and Bamforth, 1951: 476).

Sociotechnical theory seeks to understand the interdependency between the social system and the technical system. Behavior in one part of the organization affects other parts of the environment;

thus, organizational activity is viewed through the lens of interaction effects.

It is common for innovations to change as they are adopted and implemented. These changes can be interpreted on a continuum from the technology to the organization. Technological determinists often explain post adoption changes in innovations as the result of flawed design—an “engineer’s fallacy” that assumes that the technology itself is the problem. Sociotechnical theory offers alternative explanations to the engineer’s fallacy through a social constructionist perspective that contends that the social system largely shapes use of technology. Some experts argue that the technical system and the social system both are shaped by their interactions, while others suggest that the technology is shaped by the social system, and a technology’s function and use change according to the social system in which they are applied (Sawyer and Tapia, 2005). According to this perspective, alterations or misuses of technology are functions of the user or the context in which the technology is implemented.

Cityscape 11Cronley

Sociotechnical theory aims to resolve the conflicts between the technical system and the social system by achieving joint optimization, by making the social structure and the technical structure complement and support each other and the environment (Pasmore et al., 1982). Cooper and Foster (1971: 472) describe this optimization as an organizational choice, meaning “that there is an element of choice in designing effective work systems and that this choice must take into account the mutual de-pendence of the social and technical systems.” Margulies and Coleflesh (1982) report that failure to account for this mutual dependence causes misfits between the social system and the technical system, ultimately resulting in increased production costs and misuse or rejection of technology. If an organization requires staff members to devote work time toward learning and using a new technology, without decreasing other responsibilities, levels of stress and frustration among these individuals may rise. These individuals may react by refusing to learn the technology or altering its design or intended use to better match their work environments.





Thus, to support the adoption and implementation of technologies, organizations often have to change aspects of their work processes. According to organizational culture theory (Schein, 1992), this change in process occurs by first altering the values, beliefs, and expectations about behavior in the work environment. Schein drew upon open systems theory when articulating his idea of organizational culture. Open systems theory views organizations from a biological model, where they exist within changing and unpredictable environments, with constant interactions between the two (Emery and Trist, 1965). Organizations that survive are those that successfully adapt to the changing environment.

Culture incorporates both structure, such as size and levels of authority, and ideology, such as openness to change. Organizational culture describes how the work is done in an organization and is measured as the behavioral expectations reported by members of the organization. These expectations guide the way employees approach work and socialize new employees in the priorities of the organization (for example, rigidity and proficiency). Organizational culture is often described as layers, with behavioral expectations representing an outer layer and values or assumptions representing an inner layer (Homburg and Pflesser, 2000; Schein, 1992). Stated another way, Hofstede (1998) described behavior as the visible part of culture and values as the invisible part.

Schein identified three parts to organizational culture: artifacts, values and beliefs, and underlying assumptions. The artifacts and articulated values and beliefs are the explicit manifestations of the implicit assumptions. Because of this nested relationship, culture is sometimes described as a “deep” construct. Studying only the cultural artifacts (for example, organizational charts or surveys) of an organization can be misleading if they are misinterpreted. Just as an archeologist may misrepresent a piece of pottery from a civilization with which they are unfamiliar, a social theorist may interpret official manuals, charts, or accounts of responsibility inaccurately. Staff members will state values and beliefs and say that they guide behavior and expectations in the organization, but the values and beliefs may not translate into action. For example, underlying assumptions may cause staff members to follow instructions from a peer who is regarded as the expert in a certain area rather than from an official supervisor. These underlying assumptions define the foundations of an organizational culture, but because they are mostly unstated, or even unconscious, they are also the most difficult to examine. Studying organizational culture requires piecing together all components and identifying consistencies and patterns that suggest specific values, norms, and behavior.

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Recently, however, studies have suggested that culture is transmitted among employees more through behavioral expectations than through deeper values or assumptions (Ashkanasy, Broadfoot, and Falkus, 2000; Hofstede, 1998; Hofstede et al., 1990). This transmission occurs because individuals in an organization can comply with behavioral expectations without necessarily internalizing the values and assumptions that contribute to those expectations. Expectations can also be determined by the demands that workers face on the job, regardless of the values of top management (Hemmelgarn, Glisson, and Dukes, 2001). For instance, official safety measures may be relaxed in the face of tight deadlines.

A recent study that examined the relationship between organizational culture and organizational performance, specifically among nonprofit organizations, is Jaskyte and Dressler’s (2005) study of organizational culture and innovativeness. The study was based on survey results from 20 organizations and tested the model that cultural consensus and values affect innovativeness concurrently with organizational size and transformational leadership. Results showed that cultural consensus was negatively associated with innovativeness.

In summary, organizational change occurs through a dynamic process of communication and activity among interrelated social networks; the external environment, such as funders and policymakers; and the internal environment of the organization. The key components of this change are social systems or networks, the external and internal environments, and interactions.

DOI theory (Rogers, 2003) identifies the role of social systems in the spread of new ideas, while sociotechnical theory (Trist and Bamforth, 1951) explains how social systems facilitate diffusion in organizations. Both theories argue that interaction between the social system and the technical system determines the “fit” of the technology in the organization. To optimize this fit between the social and technical systems, however, we need to examine those components of the culture that guide behavior, values, beliefs, and unconscious assumptions, as described in organizational culture theory (Schein, 1992). This study, then, explores the relationship between organizational culture and implementation of an HMIS among homeless-services providers. The study first hypothesizes that characteristics of organizational culture are related to staff members’ use of an HMIS within an organization. The study then predicts that individual characteristics interact with organizational culture to affect staff members’ use.

Methodology The study is a multilevel analysis of organizational culture and staff members’ behavior, meaning that it examines hierarchical relationships between two groups. It is an exploratory analysis intended to consider if and how organizational culture may affect individual behavior. The study was also designed to assess the use of technology in the homeless services. Organizational culture characteristics were captured at one point in time to predict the frequency of HMIS use by staff members during the previous year.

Sample The study employed a purposive sample drawn from two sampling frames: (1) the East Tennessee Coalition to End Homelessness (ETCEH) and (2) the Michigan Coalition Against Homelessness

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(MICAH). ETCEH is a coalition of multiple homeless-services providers, defined by HUD as a Continuum of Care (CoC). The ETCEH CoC, in partnership with the University of Tennessee, operates its own HMIS, independent of other CoC in the state. Of the 8 organizations in the ETCEH, 7 participated in the present study. MICAH is a statewide coalition that administers a single HMIS used by multiple CoCs; 3 CoCs chose to participate in the study, one rural and two urban. In the rural CoC, 8 out of the 9 organizations using the HMIS participated. In the first urban CoC, 5 out of the 11 organizations using the HMIS participated in the study; in the second, 6 out of the 14 participated. Organizations chose not to participate for various reasons. In the rural CoC, a single organization that serves domestic violence victims declined to participate based on privacy concerns for its clients. Other organizations stated that their staff members were too busy or had only one or two staff members, making it impossible to measure their organizational culture. Finally, several organizations did not respond to repeated phone calls and e-mails.

In the final sample, level one included 142 staff members (77 percent female; 36 percent from Tennessee). Staff members were nested in 24 organizations (7 in Tennessee) at level two. These organizations were divided among emergency shelters (n = 3), transitional housing (n = 6), permanent housing (n = 7), and ancillary services (n = 10). Organizations were nested in four CoCs (the ETCEH and three from MICAH).

Data Collection The study relied on HMIS archival data to measure HMIS use during two multiple-month periods (March 1, 2007, through December 31, 2007, for ETCEH; January 1, 2008, through December 31, 2008, for MICAH). HMIS software assigns a unique identifier to all staff members who use the system. Each time a staff member logs on, the software records the date and the user’s activities, such as new clients added and services recorded. An HMIS report was created that included HMIS use among staff members, organizational affiliation, CoC, and gender. HMIS data from ETCEH and MICAH were collapsed into one data set.

Surveying staff members at participating organizations collected organizational culture data, using the Organizational Social Context (OSC) questionnaire (Glisson et al., 2008), described below.



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