A co-organizing view of the impact of variant executions and context irregularity on service errors in the waste collection sector Scott F. Turner R. H. Smith School of Business Van Munching Hall University of Maryland College Park, MD 20742 Tel: 301-405-7186 Fax: 301-314-8787 sturner@rhsmith.umd.edu Violina Rindova McCombs School of Business University of Texas-Austin Austin, TX 78712 Tel: 512-471-7975 Fax: 512-471-3937 violina.rindova@mccombs.utexas.edu Version: April 30, 2007 1 A co-organizing view of the impact of variant executions and context irregularity on service errors in the waste collection sector ABSTRACT This study examines the impact of routine functioning on error generation in a services setting. From one view, routine functioning is said to have beneficial effects in the form of developing skills that reduce errors, but an alternative view suggests detrimental effects as corresponding tendencies towards mindless behavior increase the risk of errors. To better understand the effect of routine functioning on error generation, we examine contextual conditions more closely. We distinguish between two types of context in which routines are executed: a larger objective context and a local enacted context. Collectively, we argue that the objective context in which routines are executed, the enacted context created by historical executions, and the current execution of the routine jointly determine the generation of service errors. We test our hypotheses in the context of municipal waste collection for one of the largest cities in the United States, finding evidence that is consistent with our arguments. 2 INTRODUCTION In organizational theory and strategy, routines are a central concept (Hannan and Freeman, 1984; March and Simon, 1958; Nelson and Winter, 1982; Stene, 1940). As repetitive patterns of action involving interdependent actors, routines provide a powerful concept for explaining the behavior of organizations. Central to the routine-based perspective is the efficiency criterion (Karim and Mitchell, 2000), which is manifest at multiple levels within organizations. For individuals, routines foster the development of habits that provide cognitive and behavioral efficiency (James, 1914/1890; Simon, 1976/1945). At group and organization levels, routines enable efficient means of coordination and governance (Coriat and Dosi, 1998; Gersick and Hackman, 1990; Nelson and Winter, 1982), and these efficiencies stem in large part from the organizing process, whereby routines enable the fusing together of individual-level habits (Cohen and Bacdayan, 1994; Weick, 1979). Across this body of work, substantial attention is directed to efficiencies in the productive and governance costs required to generate a focal product or service (Karim and Mitchell, 2000). However, we have less consensus regarding the impact of routine functioning on the quality of the generated product or service. Some scholars suggest beneficial effects of routine functioning, as it facilitates skill development which leads to higher-quality outputs (James, 1914/1890; Nelson and Winter, 1982). Further, ecology scholars suggest that consistency generates external value in the form of conferred legitimacy from stakeholders (Hannan and Freeman, 1984). By contrast, a habits-based stream of research suggests detrimental quality effects from routine functioning, as its tendency towards mindless behavior results in inappropriate actions and greater risk of errors (Cohen and Bacdayan, 1994; Gersick and Hackman, 1990). The purpose of this study is to examine the implications of routine functioning for error generation in a services context. While learning scholars have placed increasing interest on the study of organizational errors (Haunschild and Sullivan, 2002), this phenomena is important for routines scholarship as well (Weick, 1987; Weick and Roberts, 1993). Errors can range from the minor to the catastrophic, and we note that researchers highlight the importance of developing our understanding of the small-scale errors (Repenning and Sterman, 2002). Such errors are pervasive, have learning value, and are often focal outcomes in their own right (i.e. customer satisfaction). Further, catastrophic errors research emphasizes the tendency for small-scale errors to propagate into large-scale disasters (Perrow, 1984; Weick, 1987). In particular, we focus on service errors to better understand the process failures that occur at the boundaries of organizations, where organizations intersect with their customers. In this paper, we view routines as interaction patterns that organize the behavior of employees and co-organize the behavior of customers. We make two core arguments. First, consistent with past research, we view the execution of routines as context dependent (Cohen, et al., 1996; Nelson and Winter, 1982). Specifically, the current execution of a routine is shaped by the regularity of its larger contextual conditions. Second, in departure from past research, we view the execution of routines as context creating. This arises as the recurring nature of routine execution enacts an interlocking structure between employees and customers (Turner and Rindova, working paper; Weick, 1979). Moreover, the extent of variation in the recurring 3 executions affects the degree of "structuring" in this local, enacted context -- thereby influencing the subsequent flexibility and effectiveness of the routine. In our view, the objective context in which routines are executed, the enacted context created by past executions, and the current execution of the routine jointly determine the extent of error generation. We test a corresponding set of hypotheses in the context of municipal garbage collection for one of the largest cities in the United States in 2005, and the results provide evidence consistent with our arguments. THEORY DEVELOPMENT In routines theory, variation and consistency are the two dialectical opposites that capture the central tension in executing organizational processes and deriving benefits from routine functioning. While routines are characterized by their substantive similarity in sequences of action across executions (Cohen and Bacdayan, 1994; Cohen, et al., 1996), variation is also present in these action sequences (Feldman and Pentland, 2003; Pentland, 2003). Further, while routines scholars suggest that consistency provides efficiency benefits by automating the organizing process, a mindless view of automating human action suggests a simultaneous increase in the risk of process failure. Service errors are an important form of process failure (Tucker and Edmondson, 2003). These errors are instances in which an organization fails to provide service or incorrectly provides service to customers. By contrast with traditional efficiency metrics, errors capture an effectiveness dimension of process outcomes. Errors represent important indicators of effectiveness for a wide range of services organizations, including health care (Tucker and Edmondson, 2003), air transport (Haunschild and Sullivan, 2002; Weick and Roberts, 1993), and power generation (Perrow, 1984). In services settings, we note that greater levels of behavioral interaction between organizations and their customers can increase the incidence of errors. Greater behavioral interaction arises for many forms of service provision, as the customer must first provide an input. For example, healthcare requires patients to supply medical conditions, education needs the presence of students, and garbage collection requires customers to supply waste materials. Service errors can be small- or large-scale. While rare and catastrophic errors understandably attract substantial attention, it is interesting to observe that examinations of these large-scale failures often refocus our attention on the importance of small-scale errors as originating sources for catastrophic failure (Gersick and Hackman, 1990; Perrow, 1984; Weick, 1987). Yet, existing research provides limited understanding of the relationship between organizational processes, such as routines, and the generation of small-scale errors. Variant Execution and Context Irregularity In this study, we argue that two forms of variant executions, historical and current, and context irregularity collectively influence the generation of service errors. Historical variant executions represent the extent of sequential variety associated with prior executions of the routine (Pentland, 2003). Thus, this concept captures the extent to which the action sequence of the routine has been consistently executed in the past. Current variant executions capture the extent 4 to which the current execution of the routine departs from its historical executions, representing the degree to which the current action sequence is dissimilar from preceding executions of the routine. Context irregularity represents the extent to which the larger context in which routines are executed is dissimilar from its regular state. While some change is always present across contexts for execution, context irregularity refers to changes in the larger context that have more substantive consequences for routine functioning (Gersick and Hackman, 1990; Wood, Tam and Witt, 2005). Context as Objective and Enacted For routines theory, "context dependence is fundamental; the effectiveness of a routine is not measured by what is achieved in principle but by what is achieved in practice; this generally means that the routine might be declared effective in some specific contexts, but perhaps not in others" (Winter in Cohen, et al., 1996: 662). Moreover, scholars emphasize that multiple facets of context influence routine functioning and effectiveness. In particular, scholars direct attention to the dependence of routines on local context, which complements the functioning of a specific routine, and the larger context, which represents the objective environment within which routines are executed (Cohen, et al., 1996; Nelson and Winter, 1982). While scholarly attention has been directed to the determining effect of context on the execution of routines (Becker, 2004; Cohen, et al., 1996), we argue that historical routine executions also enact local context. Given the complementary nature of routines and their contexts, we propose that historically-enacted context and current variant executions jointly determine service error generation. With greater variation in historical executions, there is less enactment of the localized context, less co-organizing constraints from customers, and more mindful employee actors. This results in fewer process failures, as greater employee mindfulness and greater organizational slack facilitate absorption of various disturbances encountered during routine execution. Yet more variant current executions result in greater service errors as the current execution departs from established contextual support mechanisms. Moreover, we argue that there is an interactive effect. Greater consistency of historical executions results in greater enactment of local context, such that the routine becomes more dependent on the local context, and current variant executions are more likely to lead to service errors. We also consider dependence on the larger objective context. We argue that given complementary routine-context relationships, error generation is also determined by the objective context and its alignment with current executions. As there is greater irregularity in the objective context, employees and customers have less supporting structure to prompt and guide their task-related actions, suggesting that greater likelihood of errors. But irregular contextual conditions reduce the positive effect of current variant executions on error generation, as context irregularity adjusts employee and customer expectations for variant current executions. Figure 1 illustrates routine execution as context dependent and context creating. HYPOTHESES Our first hypothesis focuses on the relationship between context irregularity and service errors. Context dependence is a fundamental premise in the routines and habits literatures (Cohen, et al., 5 1996; Nelson and Winter, 1982; Wood, Tam and Witt, 2005). Routines and habits are established within particular contexts, and the recurring stimuli and structure from the context prompt and support established patterns of action (Becker, 2004; Wood, Quinn, and Kashy, 2002). For instance, the ability to execute an operating routine in a manufacturing plant requires that complementary equipment be available and arranged in the manner in which the actors in the routine are accustomed. Similarly, for services like overnight delivery, relevant contextual features include days (e.g., weekday vs. weekend) and weather conditions (e.g., clear vs. blizzard). These factors influence transit patterns and were accounted for in routine establishment, and they impact the extent to which actors in the routine receives supporting structure from the execution context. Thus, when the context changes from regular to irregular, the fit between the routine and context is disrupted, and the likelihood for errors increases. Hypothesis 1. The greater the context irregularity, the greater the number of service errors. While the objective context can generate unpredictable variations in obvious ways, we suggest that the historical executions of a routine generate a local enacted context, which is defined by the historically-recurring exchanges between the organization and its customers. These repeated exchanges create a local context that is routine-specific because they structure the interaction patterns among employees and between employees and customers (Turner and Rindova, working paper; Weick, 1979). Moreover, depending on the degree of consistency in past executions, this context will vary in the degree of structuring, and therefore in the flexibility it affords participants. First, consider the role of organizational employees. With greater variation in historical executions, employees retain a state of mindfulness in task execution (Levinthal and Rerup, 2006; Weick and Roberts, 1993). By contrast, low variation in historical executions tends to promote a state of mindless task processing, which increases the risk of misapplied habits and routines with corresponding error consequences (Gersick and Hackman, 1990; Zellmer-Bruhn, 2003). Thus, with greater variation in historical executions, employees are more likely to engage in mindful information processing and less likely to make errors associated with the "blind spot" property of routines (Cohen and Bacdayan, 1994). Next, consider the role of customers. As noted previously, in many services settings, customers are both suppliers and recipients in service arrangements (e.g., healthcare, air travel, postal service). As such, organizations typically establish formal rules to govern the terms of exchange with their customers (March, Schultz, and Zhou, 2000; Weber, 1991/1948). For instance, with air travel, passengers must arrive at the gate at least 20-30 minutes prior to the stated boarding time to ensure that they will be allowed to board the plane. While these formal rules may not be the only logics that govern day-to-day service exchanges, it is important to recognize that they represent the preferred governance logic for service organizations, sufficiently important to be stipulated as a formal rule. Organizations establish these rules of exchange governance to build slack into the organization-customer relationship. 6 With greater variation in historical executions, customers have less ability to predict the particular characteristics (e.g., timing) of any one service exchange and are more likely to follow the formal rule, which provides the main source of predictability in the exchange. Customers following the formal rules provide service organizations with greater slack to perform the service in the face of inevitable process disturbances, reducing the likelihood of errors. However, the recurring nature of executions result in a structured enacted context, as service engagements take the form of environmental stimuli for customers. Consistently-recurring stimuli enable customers to develop expectations and habits for typical service exchanges. This facilitates a co-organizing process between customers and organizations, enabling customers to evolve from governed by the formal rule to governed by their co-organized habits (Turner and Rindova, working paper; Weick, 1979). This reduces organizational slack for handling inevitable process disturbances and increases the likelihood of errors due to misaligned organization-customer exchanges. Thus, due to its effects on both employee and customer behavior, we expect that as historical variation in routine executions increases, errors will decrease. Hypothesis 2. The more variant the historical executions, the fewer the service errors. Next we propose that the effect for current variant execution is in the opposite direction of that for historical variant executions. Here we expect that more variant current executions result in greater service errors. From the organization side, employees develop work habits and routines with repetitive task experience (Cohen, et al., 1996; Weick, 1979). Such habits and routines are embedded in particular contextual structures, which facilitate smooth performance of the execution. With a more variant current execution, employees face a reduction in the structural support to which they have become accustomed, resulting in greater likelihood of generating service errors. A similar pattern unfolds on the customer side. As customers share recurring exchange experiences with an organization, they are more likely to co-organize themselves with the routine (Turner and Rindova, working paper). The co-organizing process is supported by coaligning temporal structures, like time of day or week, which psychologists identify as particularly strong guides to habitual behaviors (Wood, Neal and Quinn, working paper). For instance, if a mail carrier arrives every day at 2pm, customers are likely to establish outgoing mail habits centered on this time -- even if departs substantially from the formal rule for having outgoing mail ready. As a result, with a more variant current execution, customer actions in the exchange relationship are more prone to misalignment, increasing the risk of errors. Returning to our example, if the mail carrier arrives at an unexpected time of 10am, the likelihood of undelivered mail increases due to greater misalignment with co-organized customer habits. Hypothesis 3. The more variant the current execution, the greater the service errors. Our fourth hypothesis expects that greater context irregularity will diminish the positive effect of current variant execution on service errors. Recall the basic argument for the current variant 7 execution effect as follows. For employees, the increasing likelihood of errors stems from established employee habits firing in variant manners with limited contextual familiarity and support. Similarly, for customers, errors are more likely as the recurring organizational pattern of service, which provides a form of stimuli-based structure, is disturbed and misaligns with the customers' co-organized habits. Given that baseline, as context irregularity increases, both employees and customers reduce their expectations for routine functioning. For employees, this increases the mindfulness of their behavior, and for customers, it can serve to untie their co-organized habits, increase their propensity to act in line with the formal rules, and provide greater organizational slack. Thus, greater context irregularity will have a dampening effect on the positive effect of current variant execution on service errors. Hypothesis 4. The greater the context irregularity, the lower the effect of current variant execution on service errors Our last hypothesis predicts that greater historical variation in executions will reduce the positive effect of current variant execution on service errors. Our argument for the current execution effect leads to error generation due to misfit between current variant executions and established habits for executing the routine. In other words, with greater variation in historical executions, employees develop weaker habits, retain more mindful behavior, and are less likely to generate errors during a current variant execution. Similarly, more variant historical executions result in less consistent organization-provided stimuli for customers, such that customers are less likely to establish habits that co-organize their behavior to align with the organizational routine. As such, under conditions of more variant historical executions, current variant executions are less likely to result in service exchange problems with customers. In sum, we expect historical variation in executions to reduce the positive effect of current variation execution on service errors. Hypothesis 5. The more variant the historical executions, the lower the effect of current variant execution on service errors. DATA AND METHODS Data Our empirical setting is one of municipal services, specifically the collection of garbage. Garbage collection has several characteristics that are particularly appropriate for studying routines. First, the routines literature identifies repetition and action interdependence as key elements behind the emergence of a routine (Becker, 2004; Stene, 1940). Waste collection is a repetitive task, as garbage service is provided weekly for each household. Notable interdependence of actions is present in this setting, as field staff interact with others in the organization (e.g., peers, supervisors), with customers, and with the general environment (e.g., dogs, pedestrians). Second, routines scholars highlight the challenges of routine identification (Becker, 2004; Cohen, et al., 1996). In this setting, routines are clearly delineated in terms of geography and time. Routines are classified geographically in terms of routes, which are distinct 8 geographic domains for which service is to be provided each week, and each routine is bounded temporally within the confines of a typical work-day. Our specific empirical context is the collection of garbage in the city of San Diego. San Diego is one of the ten largest cities in the United States, and its Environmental Services Department is at the leading edge of capturing service delivery data through sophisticated information systems. Data supplied by the Environmental Services Department spans three domains. Service errors are obtained from the department's work order system. Variant executions are captured with a technique for determining the dissimilarity between sequences; this approach is utilized in diverse areas from molecular biology to sociology to human language to bird songs (Abbott and Hrycak, 1990; Kruskal, 1983; Pentland, 2003). Spatial locations of service delivery events (i.e., waste collection pick-ups) are identified with geographical information systems software, such that standard collections (i.e., within the route domain) can be identified as distinct from atypical work tasks undertaken by crews (i.e., collection pickups made outside the route domain). Each data component is initially processed independently and then integrated together for subsequent statistical analysis. The dataset includes seven months of data from June 2005 through December 2005. We used the first two months, June and July, in setting a baseline for historical variant executions. Therefore, we conducted statistical analysis on five months of data: August 2005 through December 2005. Due to data magnitude and corresponding management challenges, our analysis focused only on Monday garbage collection routes. Within the population of approximately 70 Monday routes for the organization, we randomly selected 22 routes for analysis. Routes are served by one-person waste collection crews that execute routines utilizing automated equipment technology. The level of analysis is the routine execution-day. For one collection day, November 21, data was not available for any routes due to systemic problems with the information monitoring systems. Excluding this day, data was missing for 18% of the sample. To gain additional insight as to the randomness of missing data, we requested additional information for a subset of missing data from IT administrators with the department. Their response indicated that the missing data was largely due to periodic failure with data capture elements of the information monitoring system (e.g., failure of a GPS unit). Therefore, for purposes of our analysis, we can treat the data as missing at random, and we performed listwise deletion for the related observations (Roth, 1994). Variables Table 1 presents descriptive statistics for the variables. Dependent variable Our dependent variable, Service Errors, is a count of the number of customer and supervisor reports of missed collection service. The information systems identified each incident (i.e., service error) by route and by reporting date. We aggregated all service errors reported between the day of routine execution and the sixth day following the execution and treated this value as the number of service errors for that day of routine execution. Between August 2005 and 9 December 2005, we observed 335 service errors reported across all the routes. The range of service incidents per route-execution day was 0 to 19. Explanatory variables Context Irregularity was operationalized with a binary variable that indicated whether the typical collection service day fell on a city-observed holiday. Between August 2005 and December 2005, there were two city-observed holidays that occurred on Mondays: Labor Day on Monday, September 5, and Christmas on Monday, December 26. Our operationalized variable, City Holiday, was coded as a 1 if route executions fell on one of these two days, and 0 otherwise. Historical Variant Executions and Current Variant Execution were operationalized with an optimal string matching technique (Abbott and Hrycak, 1990; Kruskal, 1983; Pentland, 2003). The technique captures dissimilarity between sequences in terms of the insertions, deletions and substitutions required to transform one sequence into another sequence. The Levenshtein distance determines the least costly set of insertions, deletions and substitutions and represents the cost of sequence transformation. Consistent with prior work, we set the cost of each transforming operation to 1, and for a given set of sequences, we use the average of distances between pairs of sequences for operationalization (Pentland, 2003). For Historical Variant Executions, for a given route execution, we calculated the average distance among all execution sequences for that route within the prior 30 days. For Current Variant Execution, we calculated the average distance between the current execution sequence and all execution sequences for that route within the prior 30 days.1 Control variables To account for potential influences from change in task load (Gersick and Hackman, 1990), we controlled for work load by including three measures. City Work Load represents the average number of waste collections made by all crews in the sample on the focal day. Route Work Load indicates the number of waste collections made by a crew on the focal routine execution day, and Route Additional Work Load represents the number of waste collections made by the crew outside its route for the focal execution day. To account for employee experience (Gersick and Hackman, 1990; Wood, Neal and Quinn, working paper), we included a Route Experience variable, which indicates whether the field employee had executed collections on this route within the past 30 days. We also accounted for potential entraining effects associated with start times (Bluedorn, 2002). For start times, we controlled for variation in past task start times as well as the divergence of the current start time relative to that of prior executions. For a given route execution, Past Start Time Divergence is the average of the absolute values of the start time difference in minutes between all execution days for that route within the past 30 days. Current Start Time Divergence is the average of the 1 We based the 30-day window on related qualitative research by the authors in a similar solid waste collection context. In that research, informants indicated that employees typically form related work habits and routines within 4-6 weeks following the initiation of employment or a major organizational change. Given the computational demands of the calculations, we focused on the 30-day window. 10 absolute values of the difference between the start time of the current route execution day and the start times of all executions for that route within the past 30 days. Models and Analysis We employed a Poisson regression model for analyzing the data and included fixed effects for the routes. In separate analyses, we considered two robustness examinations for the model, focusing on the potential for overdispersion to bias standard errors. Our sensitivity analyses employed a fixed effects Poisson model with bootstrapped standard errors as well as a negative binomial conditional fixed effects model. The sensitivity analyses provided substantively similar results to those presented in Table 2. RESULTS Table 2 reports our analyses using a nested approach to examine the empirical evidence for our hypotheses. All models included fixed effects for the route. As a baseline, Model 1 included all the control variables. Models 2 through 6 added the explanatory variables independently, and Model 7 added the explanatory variables simultaneously. Model 2 addressed Hypothesis 1, which predicts that service errors will be greater in irregular contexts. We expected a positive coefficient for collections associated with city-observed holidays, and we found strong support (p<0.01). Hypothesis 2 was examined with Model 3. This hypothesis expects that as historical variant executions increase, there will be fewer service errors. Consistent with our prediction, we found a negative coefficient (p<0.01). Thus, our results support Hypotheses 1 and 2. Hypothesis 3 expects that the more variant the current execution, the greater the service errors. We addressed this hypothesis with Model 4, and we observed a positive and significant coefficient (p<0.05), indicating support for Hypothesis 3. In Models 5 and 7, we examined Hypothesis 4. Our expectation is that city-recognized holidays will have a dampening effect on the positive effect of current variant execution on service errors. However, we did not find statistical support for Hypothesis 4. We discuss this finding in greater detail below. Finally, Models 6 and 7 addressed Hypothesis 5. We expected that more variant historical executions will reduce the positive effect of current variant execution on service errors. We observed a negative coefficient for the interactive term (p<0.01), and thus we find support for Hypothesis 5. Extending Analysis As noted above, we did not find statistical support for Hypothesis 4. This hypothesis states that the positive effect of current variant execution on service errors will be reduced in irregular contexts. A key element of our argument is that customers have lower expectations for consistent executions when contextual conditions are disturbed. But for this effect to be present, customers must recognize the disturbed context. We conducted an extending analysis to examine whether the "magnitude" of the holiday may influence our results. 11 Within our empirical window of August-December 2005, there are two city-recognized holidays: Labor Day and Christmas. In the United States, customers are more likely to expect Christmas as a city-recognized holiday relative to Labor Day. With this in mind, we separated the two holiday event variables (i.e., Christmas as the more recognized holiday) and reanalyzed the results. For the main effect of holiday (Hypothesis 2), we observed positive coefficients for both holidays, but the results were only statistically significant for the Christmas holiday (p<0.01). For the interaction between the Labor Day holiday and current process divergence, we observed a positive coefficient that was not significant. By contrast, and consistent with our rationale for Hypothesis 4, we observed a negative and significant coefficient for the interaction between the Christmas holiday and current variant execution (p<0.05). DISCUSSION The objective of this study was to gain a better understanding of the consequences of routine functioning for error generation in a services setting. We proposed that routine functioning is both context dependent and context creating. Specifically, routine functioning is dependent upon the larger, objective context that provides recurring and supporting structure for executions. At the same time, the consistent nature of routine executions enacts a local context, which structures an interlocking of habits between employees and customers. Moreover, we propose that greater variation in the current execution of the routine leads to greater error generation, particularly when the local, enacted context is firmly established by historical consistency and when conditions are regular for the larger, objective context. Our findings are consistent with the proposed theory, and we offer related implications for the literatures that examine routines, organizational errors and high-reliability organizations. Implications for the Routines Literature Our findings suggest implications for the routines literature in terms of context enactment and context dependence. First, while the consistencies associated with routine functioning enable efficiencies (Cohen and Bacdayan, 1994; Weick, 1979), in the process of enactment, they simultaneously lead to tighter coupling with exchange partners. In certain instances, tighter coupling may be advantageous as suggested by research on the formation of inter-organizational routines between organizations and suppliers (Kotabe, et al., 2003) and between those of alliance partners (Zollo, et al., 2002). But at the same time, in enacting interlocked structures with customers, organizations reduce slack for task completion, have additional challenges associated with managing stakeholder linkages, and face greater risk of process failure. For organizations, this implies the presence of an efficiency-robustness trade-off associated with consistency of execution. Second, we contribute to the idea of context dependence by distinguishing between the historically-developed enacted context and the exogenously-determined objective context. While contextual conditions have a constraining effect on routine execution, our findings have implications for the conditions under which routines have greater flexibility for change and experimentation. For the enacted context, it suggests that routines are more flexible when the routine is nascent to the context or when there are points of substantial turnover among 12 stakeholders. From a planning perspective, organizations that anticipate future changes may choose to introduce more variant executions in efforts to begin to unravel the interlocked structure between organizations and customers. Alternatively, organizations may seek to align changes or experiments during irregular times for the objective context, as stakeholders expect less consistency in routine functioning. Organizational Errors and High-Reliability Organizations This study also contributes to our understanding of the determinants of organizational errors, a pervasive phenomena that has received limited conceptual and empirical attention in organizational theory (Haunschild and Sullivan, 2002). But emerging scholarly interest is reflected in two areas. One stream of research focuses on learning theories and adopts a backward-looking view, examining how organizations learn from past errors (Haunschild and Sullivan, 2002; Sitkin, 1992; Tucker and Edmondson, 2003). Another stream examines highreliability organizations with a forward-looking view, focusing on how organizations anticipate and prevent errors (Weick, 1987; Weick and Roberts, 1993). The role of variety is a key theme in both streams of research. In the backward-looking area, scholars argue that organizations reduce error rates based on the information diversity embedded in past errors, and correspondingly find that organizations with greater heterogeneity in past error incidents have lower rates of subsequent error occurrence (Haunschild and Sullivan, 2002). From the forward-looking stream, Weick (1987) argues that high reliability organizations, or those with ongoing low rates of error occurrence, benefit from greater variety in the organizational system that monitors for signals of potential problems. Our study contributes to this literature in the linkages among variety, slack and error generation. In research on high-reliability organizations, two central issues are reliability and organizational slack. Weick (1987) emphasizes that one means by which organizations achieve a highreliability state is by building organizational slack. Our study findings reveal an important tension. As organizations become more reliable in their routine executions, they reduce the organizational slack that can inhibit error generation. This arises as customers receive reliable service executions as consistent environmental stimuli to which they evolve and co-organize their behavior. Moreover, it draws attention to tension within the concept of high-reliability organizations (e.g., highly-reliable, low-error organizations). Specifically, we find that the value of variety partially stems from unreliable organizational functioning, which enhances mindfulness, preserves organizational slack, and loosens coupling between organizations and stakeholders. In sum, this study enhances our understanding of the role of context in routines theory. While previous research emphasizes the context-dependent nature of routines, this study finds that routines are both context dependent and context creating, with corresponding implications for the effect of routine functioning on error generation. 13 REFERENCES Abbott A, Hrycak A. 1990. Measuring resemblance in sequence data: An optimal matching analysis of musicians' careers. American Journal of Sociology 96(1): 144-185 Becker MC. 2004. Organizational routines: A review of the literature. 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Management Science 49(4): 514-528 Zollo M, Reuer JJ, Singh H. 2002. Interorganizational routines and performance in strategic alliances. Organization Science 13(6): 701-713 16 Figure 1. Routine Executions as Context Dependent and Context Creating Objective context Objective context • context dependence • context as supporting and prompting executions Executions of routine • context creating • executions as structuring and co-organizing Enacted context Enacted context Historical Executions Current Execution Time 17 Table 1. Variable Summary Statistics and Product-Moment Correlations (N = 273 routine-day executions) 1 2 3 4 5 6 7 8 9 10 11 12 Variable ServiceErrors CityWorkLoad RouteWorkLoad RouteAdditionalWorkLoad RouteExperience PastStartTimeDiverge CurrentStartTimeDiverge CityHoliday HistoricalVariantExecution CurrentVariantExecution CityHoliday*CurrentVariantExecution HistoricalVariantExecution*CurrentVariantExecution 1 2 3 4 5 6 7 8 9 10 11 12 Variable ServiceErrors CityWorkLoad RouteWorkLoad RouteAdditionalWorkLoad RouteExperience PastStartTimeDiverge CurrentStartTimeDiverge CityHoliday HistoricalVariantExecution CurrentVariantExecution CityHoliday*CurrentVariantExecution HistoricalVariantExecution*CurrentVariantExecution Mean 1.16 536.21 591.44 122.15 0.87 23.03 21.71 0.11 0.64 0.65 0.08 0.42 StdDev 2.39 109.88 397.35 253.96 0.34 29.25 27.11 0.31 0.12 0.12 0.22 0.13 Min 0.00 0.00 0.00 0.00 0.00 0.67 1.33 0.00 0.34 0.34 0.00 0.12 Max 19.00 696.75 2318.00 1472.00 1.00 152.00 207.00 1.00 0.88 0.99 0.93 0.73 1 1.00 -0.07 0.07 -0.04 -0.20 0.03 0.04 0.24 -0.05 0.18 0.24 0.05 2 3 4 5 6 7 8 9 10 11 12 1.00 0.26 -0.03 -0.03 0.13 0.00 -0.05 -0.03 -0.23 -0.05 -0.15 1.00 -0.22 0.12 -0.10 -0.17 -0.03 -0.10 -0.25 -0.05 -0.19 1.00 0.01 0.07 0.03 -0.06 0.03 0.06 -0.06 0.04 1.00 -0.03 -0.01 -0.11 0.02 -0.43 -0.13 -0.22 1.00 0.51 0.14 0.33 0.19 0.16 0.32 1.00 0.05 0.18 0.27 0.07 0.27 1.00 0.08 0.18 0.99 0.15 1.00 0.55 0.10 0.89 1.00 0.22 0.86 1.00 0.19 1.00 Variable Description Number of reported garbage collection misses or customer call requests Average number of garbage collections made across all routes in the sample Number of within-route garbage collections made Number of outside-route garbage collections made Employee experience on the route (1 if the employee has collected in this route within past 30 days, 0 otherwise) Absolute Value of the average differences in route execution start times within past 30 days Absolute value of the difference between the current route execution start time and that of all historical route executions within past 30 days Context Irregularity (1 if typical collection day is a city-recognized holiday, 0 otherwise) Average of the Levenshtein Distance between all route executions within the past 30 days Average Levenshtein distance between the current route execution and that of all historical route executions within past 30 days Interaction between City Holiday and Current Variant Execution Interaction between Historical Variant Execution and Current Variant Execution 18 Table 2. Poisson Regression Estimates for Service Errors, with fixed effects for the routes N = 257 routine-day executions, with one set of route observations dropped due to invariance in service errors 1 Coeff. 2 Coeff. 3 Coeff. 4 Coeff. 5 Coeff. 6 Coeff. 7 Coeff. CityWorkLoad RouteWorkLoad RouteAdditionalWorkLoad RouteExperience PastStartTimeDiverge CurrentStartTimeDiverge CityHoliday HistoricalVariantExecution CurrentVariantExecution CityHoliday*CurrentVariantExecution HistoricalVariantExecution*CurrentVariantExecution -0.002** 0.001** -0.001 -1.081** 0.003 0.004* -0.002** 0.001** -0.001 -0.917** -0.001 0.005** 1.077** -0.002** 0.000* -0.001 -1.039** 0.007** 0.004* -0.002** 0.001** -0.001 -0.868** 0.002 0.003 -0.002** 0.001** -0.001 -0.749** -0.002 0.004 1.462 -0.002** 0.001** -0.001* -0.590** 0.009** 0.002 1.433* 1.354* -0.568 -23.195** -0.002** 0.001** -0.001* -0.442* 0.005* 0.003 0.446 15.605** 18.311** 0.925 -27.873** Model Log-likelihood -409.95** -382.629** -357.286** Explanatory Variables Control Variables Hypotheses -2.977** -385.630** ** p<0.01, * p<0.05 (one-tail tests) 19 -399.77** -408.139** -384.110** 12.264** 15.821** 20