Impact of lean manufacturing and environmental management on business performance: An empirical study of manufacturing firms

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Abstract

This paper explores relationships between lean manufacturing practices, environmental management (e.g., environmental management practices and environmental performance) and business performance outcomes (e.g., market and financial performance). The hypothesized relationships of this model are tested with data collected from 309 international manufacturing firms (IMSS IV) by using AMOS. The findings suggest that prior lean manufacturing experiences are positively related to environmental management practices. Environmental management practices alone are negatively related to market and financial performance. However, improved environmental performance substantially reduces the negative impact of environmental management practices on market and financial performance. The paper provides empirical evidences with large sample size that environmental management practices become an important mediating variable to resolve the conflicts between lean manufacturing and environmental performance. Additional contextual analyses suggest that differences exist in terms of the strengths and statistical significance of some of the proposed relationships. Thus, for effective implementation of environmental management, firms need to measure environmental performance through which the impact of environmental management on other business performance outcomes is examined.

Introduction

With an increasing social demand of environmental sustainability, firms embrace the strategic importance of environmental management practices for competitive advantage (Porter and van der Linde, 1995, Sroufe, 2003, Kleindorfer et al., 2005, Pagell and Gobeli, 2009, Yang et al., 2010). In spite of the ongoing debate on the relationships between environmental management and financial performance, the previous research is often inconsistent and ambiguous (Russo and Fouts, 1997, Jiménez and Lorente, 2001, Rao and Holt, 2005). The business press also reflects this debate among practitioners regarding the compatibility of environmental objectives with economic viability (Hayward, 2009, Stavins, 2009, Totty, 2009). In light of these divergent views, while organizations recognize that environmental sustainability has implications for their competitive positions, firms are unclear about the implementation details of environmental management practices (Montabon et al., 2007).

Good research requires rigor, relevance and clarity (Palmer et al., 2009, Suddaby, 2010). Building sound theory may start with the obvious and then move into more unclear, controversial and fuzzy areas (Handfield and Melnyk, 1998). In this paper, we start with the relationship between lean manufacturing and environment management practices. We then present an integrated framework that includes lean manufacturing, environmental management practices, and environmental and business performance. In the next section we provide a research model conceptual framework that presents key variables based on relevant literature review. In the hypotheses development section the inter-relationships between variables are defined and explained. In the subsequent section we discuss the research design, analysis and results. The final section presents the theoretical and managerial implications, and concludes with a summary of limitations and future research directions.

Section snippets

Literature review

An important task of empirical validation is to test the internal and external validity. For this reason, construct clarity is to measure what needs to measure (Suddaby, 2010). In this paper, we have carefully defined each construct in terms of essential characteristics with the support of relevant literature base. The detail measures ensure adequate construct validity. We then examine how these constructs are related. Table 1 is a summary of each construct (definitions and supporting

Hypotheses development

Fig. 1 is a research framework that represents how lean manufacturing, environmental management practices, environmental performance, market performance and financial performance are related. Specific hypotheses are discussed next.

Research database

In order to test the proposed hypotheses, we use the International Manufacturing Strategy Survey (IMSS-IV) data collected in 2005. IMSS is a worldwide research project and has been carried out since 1992 by an international network of operations strategy researchers for the purpose of identifying the strategies, practices and performance of manufacturing firms’ worldwide. IMSS data collection is conducted by the international coordinator along with national coordinators. The survey is prepared

Data analysis and results

Structural equation modeling (SEM) is used to analyze the data and its relationships (Hair et al., 1998). We follow Anderson and Gerbing’s (1988) recommended two-step approach to test our hypotheses. In step 1 we test the measurement model to establish validity and reliability of the scales used in our analysis and followed by the test of structural relationships in step 2. These are discussed next.

Concluding remarks

This research model presents lean manufacturing as an important antecedent of environmental management practices. Organizations may respond to regulations, policy and public pressure by making efforts to improve environmental performance or may choose to proactively engage in such practices. However, the results of our research must be interpreted with caution. As with all research endeavors this paper has certain limitations which provide avenues for future research. First, this research uses

Ma Ga (Mark) Yang is a Ph.D. candidate of Manufacturing and Technology Management at the University of Toledo, USA. He holds an MBA from University of Toledo and a BA from Hankuk University of Foreign Studies in Seoul, Korea. His article has been accepted in International Journal of Service Operations Management. His research interest is in sustainable supply chains focusing on sustainable environmental and social practices, environmental management, lean manufacturing and green supply chain

References (93)

  • C. Kocabasoglu et al.

    Linking forward and reverse supply chain investments: The role of business uncertainty

    Journal of Operations Management

    (2007)
  • S. Li et al.

    Development and validation of a measurement instrument for studying supply chain management practices

    Journal of Operations Management

    (2005)
  • C. Lin et al.

    A structural equation model of supply chain quality management and organizational performance

    International Journal of Production Economics

    (2005)
  • K. Linderman et al.

    Six sigma: the role of goals in improvement teams

    Journal of Operations Management

    (2006)
  • S. Matos et al.

    Integrating sustainable development in the supply chain: the case of sustainable development in the oil and gas and agricultural biotechnology

    Journal of Operations Management

    (2007)
  • K.E. McKone et al.

    Total productive maintenance: a contextual view

    Journal of Operations Management

    (1999)
  • R. McLachlin

    Management initiatives and just-in-time manufacturing

    Journal of Operations Management

    (1997)
  • S.A. Melnyk et al.

    Assessing the impact of environmental management systems on corporate and environmental performance

    Journal of Operations Management

    (2003)
  • P. Miettinen et al.

    How to benefit from decision analysis in environmental life cycle assessment (LCA)

    European Journal of Operational Research

    (1997)
  • F. Montabon et al.

    An examination of corporate reporting, environmental management practices and firm performance

    Journal of Operations Management

    (2007)
  • R. Narasimhan et al.

    Effect of supply chain integration on the relationship between diversification and performance: evidence from Japanese and Korean firms

    Journal of Operations Management

    (2002)
  • R. Shah et al.

    Use of structural equation modeling in operations management research: looking back and forward

    Journal of Operations Management

    (2006)
  • R. Shah et al.

    Relationships among information technology, inventory, and profitability: an investigation of level invariance using sector level data

    Journal of Operations Management

    (2007)
  • R. Shah et al.

    Lean manufacturing: context, practice bundles, and performance

    Journal of Operations Management

    (2003)
  • R. Shah et al.

    Defining and developing measures of lean production

    Journal of Operations Management

    (2007)
  • Q. Tu et al.

    Absorptive capacity: enhancing the assimilation of time-based manufacturing practices

    Journal of Operations Management

    (2006)
  • C. Voss et al.

    Differences in manufacturing strategy decisions between Japanese and Western manufacturing plants: the role of strategic time orientation

    Journal of Operations Management

    (1998)
  • C. Yang et al.

    Mediated effect of environmental management on manufacturing competitiveness: an empirical study

    International Journal of Production Economics

    (2010)
  • Q. Zhu et al.

    Relationships between operational practices and performance among early adopters of green supply chain management in Chinese manufacturing enterprises

    Journal of Operations Management

    (2004)
  • J.C. Anderson et al.

    Structural equation modeling in practice: a review and recommended two-step approach

    Psychological Bulletin

    (1988)
  • J.A. Aragon-Correa

    Strategic proactivity and firm approach to the natural environment

    Academy of Management Journal

    (1996)
  • J.S. Armstrong et al.

    Estimating non-response bias in mail surveys

    Journal of Marketing Research

    (1977)
  • R.M. Baron et al.

    The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations

    Journal of Personality and Social Psychology

    (1986)
  • L. Bergkvist et al.

    The predictive validity of multiple-item versus single-item measures of the same constructs

    Journal of Marketing Research

    (2007)
  • J. Blackburn

    Time-based competition: the next battleground in manufacturing

    Business One Irwin, Homewood, IL

    (1991)
  • T.J. Brown et al.

    The company and the product: corporate associations and consumer product responses

    Journal of Marketing

    (1997)
  • M.W. Browne et al.

    Testing structural equation models

  • K. Buysse et al.

    Proactive environmental strategies: a stakeholder management perspective

    Strategic Management Journal

    (2003)
  • R. Cagliano et al.

    The linkage between supply chain integration and manufacturing improvement programmes

    International Journal of Operations & Production Management

    (2006)
  • M. Christopher et al.

    Supply chain migration from lean and functional to agile and customized

    Supply Chain Management: An International Journal

    (2000)
  • W.M. Cohen et al.

    Absorptive capacity: a new perspective on learning and innovation

    Administrative Science Quarterly

    (1990)
  • L.J. Cronbach

    Coefficient alpha and the internal structure of tests

    Psychometrika

    (1951)
  • M. Delmas et al.

    Stakeholders and environmental management practices: an institutional framework

    Business Strategy and the Environment

    (2004)
  • J. Derwall et al.

    The eco-efficiency premium puzzle

    Financial Analysts Journal

    (2005)
  • S.C. Ellis et al.

    Buyer perceptions of supply disruption risk: a behavioral view and empirical assessment

    Journal of Operations Management

    (2010)
  • R Florida

    Lean and green: the move to environmentally conscious manufacturing

    California Management Review

    (1996)
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    Ma Ga (Mark) Yang is a Ph.D. candidate of Manufacturing and Technology Management at the University of Toledo, USA. He holds an MBA from University of Toledo and a BA from Hankuk University of Foreign Studies in Seoul, Korea. His article has been accepted in International Journal of Service Operations Management. His research interest is in sustainable supply chains focusing on sustainable environmental and social practices, environmental management, lean manufacturing and green supply chain management.

    Dr. Paul Hong is Professor of Operations Management at the University of Toledo, USA. Dr. Hong holds a doctoral degree in Manufacturing Management and Engineering from the University of Toledo. He also holds an MBA and an MA in Economics degree from Bowling Green State University, USA, and a BA from Yonsei University in Seoul, Korea. His articles have been published in journals including Journal of Operations Management, International Journal of Production Economics, Journal of Supply Chain Management, European Journal of Innovation Management, International Journal of Operations and Production Management, Journal of Enterprise Information Management, Journal of Knowledge and Information Management, International Journal of Quality and Reliability Management, Benchmarking: An International Journal, Strategic Outsourcing: An International Journal, Research in International Business and Finance, International Journal of Logistics and Systems Management, Korean Journal of Tourism Research, and Tourism Culture and Science. His research interests are in technology management, operational strategy and global supply chain management.

    Dr. Sachin Modi is Assistant Professor of Operations Management at the University of Toledo, USA. Dr. Modi holds a doctoral degree in Operations Management and Decision Sciences from Indiana University—Bloomington. He also holds an MS in Industrial Engineering degree from the University of Cincinnati, USA. His article has been published in the Journal of Operations Management. His research interests are in technology management, innovation, operations management and supply chain management.

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