A learning and knowledge approach to sustainable operations

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Abstract

Manufacturing's choice of environmental technologies is expected to be partly driven by the organizational context and receptivity to new ideas and innovation. More specifically, we hypothesize that the organizational learning and knowledge system of a manufacturing plant tends to favor the adoption of pollution prevention technologies and environmental management systems over pollution control technologies of that plant. The organizational learning and knowledge system is hypothesized to be split in two different stages, organizational learning antecedents and organizational learning processes. The choice of environmental technologies is hypothesized to be partially related to the organizational learning antecedents, and mediated by the organizational learning processes. Survey data exploring these relationships are presented from a sample of manufacturing plants in Canada. We found that the actual trade-off is not only between pollution prevention and pollution control, but also between pollution prevention and environmental management systems. The plant's social climate and external knowledge exchange are positively related to pollution control, while the stock of knowledge of managers, stock of knowledge of workers, and internal knowledge exchange are negatively related to pollution control. Environmental management systems had the opposite results. These results are counterintuitive, since we expected that all constructs from organizational learning culture would contribute to the choice of pollution prevention and environmental management systems. We found, however, no empirical support for the mediated model, and the organizational learning and knowledge system explained very little variance in the choice for pollution control. Our study makes three significant contributions. First, it explains, at least in part, the linkages between the stock of employee knowledge, knowledge exchange and managerial choices of environmental technologies in manufacturing. Second, it refined and validated scales that capture organizational knowledge within operations. Finally, this research highlighted the important role that plant-level social climate has on fostering a greater emphasis on pollution prevention. The managerial implications of this research are twofold. Managers, in order to promote pollution prevention and creating long term value with this kind of technology, should promote both the social climate and the external knowledge exchange in the plant. Managers also should craft their environmental management systems not as a bureaucratic process of documentation and regulatory compliance, or just to fulfill clients’ or parent company requirements, but as a source of process improvement and innovation.

Introduction

For many companies, environmental performance is becoming an important competitive criterion. However, long-term competitiveness is only possible by improving environmental performance simultaneously with other competitive criteria. Nevertheless, despite the effort of the public environmental policies (Ashford, 1993) and the claim that it pays to be green (Porter and van der Linde, 1995), many companies are still far from implementing environmental technologies and being competitive at the same time (Elgin, 2007).

The decision of investment allocation among environmental technologies can affect this relation between having environmentally sustainable operations and being competitive (Choi and Chiu, 2012). However, budget for investments in environmental technologies in manufacturing plants is also a limited, scarce resource. For this reason, plant managers must choose where to invest. Previous research has shown that some environmental technologies (namely, pollution prevention) are related to financial performance (King and Lenox, 2002). Under no restrictions, a rational manager would then always choose to invest in pollution prevention, and other forms of environmental investments would not exist. However, there is empirical evidence, in this work and others (e.g., Klassen, 2000), that managers do not allocate their entire environmental budget to pollution prevention technologies. To what conditions is the choice of allocation of environmental investments bounded? One possibility is that managers are subject to bounded rationality (Simon, 1947): they simply do not know that pollution prevention is more efficient. As March (1991) points out, the explicit choices are found in calculated decisions about alternative investments and competitive strategies, but the implicit choices are buried in many features of organizational forms and customs. Therefore, March's reasoning prompts an unaddressed research question: is the choice of environmental technologies related to the organizational learning in the plant? In this paper, we propose that organizational factors explain the choice of the environmental technologies, namely the organizational learning and knowledge system.

This research sheds light in one very important environmental management decision: the choice of environmental technologies. Consistent with the behavioral theory of the firm (Cyert and March, 1963) we claim that managers, under scarce resources, such as the budget for environmental investments, will have to make decisions, and these decisions are contingent to the tangible and intangible resources available to the manager (Grant, 1996). We investigate the extent to which the organizational learning and knowledge system influence the choice of environmental technologies. We empirically test our hypotheses on a sample of manufacturing firms. The structure of this paper is as follows: in Section 2, we provide the theory that links organizational learning and knowledge to the choice of environmental technologies, and provide our hypotheses. In Section 3, we provide the methodological procedures deployed in this paper. Following, in Section 4 we provide the analyses and results. Section 5 closes the paper by providing the discussion of the results and the conclusions of the paper.

Section snippets

Organizational learning and knowledge management

Organizational learning and knowledge management are related concepts, but derive from different research streams (Chiva and Alegre, 2005). In order to measure the impact of the organizational learning and knowledge system on the environmental technology choice, we provide some definitions that allowed us to unambiguously measure and test these constructs. Organizational learning is a topic researched mainly in organizational behavior and human resources fields, while knowledge management is a

Overview of the research process

We gathered data from a sample of Canadian manufacturing plants in the following industries: fabricated metal products, machinery, electronics, and electrical appliances (NAICS codes 332, 333, 334, and 335). The data collection took place in 2007. To test our hypotheses, we measured both the organizational learning constructs and environmental technologies with previously validated scales. We used a survey questionnaire, addressed to the plant manager, operations manager, or equivalent decision

Analyses and results

We assessed the psychometric properties of the scales of the organizational learning and knowledge using Churchill's (1979) method. From the original scales, we had only to purify the external knowledge transfer scale. We dropped 2 items from that scale: parent company and tracking new market trends in industry as source of learning. The former item, despite the fact that parent companies are very important sources of external knowledge in multinational corporations (Gupta and Govindarajan, 2000

Discussion

The purpose of this research was to identify the organizational learning and knowledge predictors in a model of the managerial choice of environmental technologies. We developed this model by first defining the organizational learning antecedents, organizational learning processes, and environmental technologies. We then connected these variables conceptually and empirically. Finally, we tested these connections, using a sample of plant managers to assess their managerial choice to allocation

Acknowledgments

The Social Sciences and Humanity Research Council (SSHRC) of Canada, HEC Montreal, and the National Council for Research (CNPq), Brazil provided financial support for this study.

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