Do human critical success factors matter in adoption of sustainable manufacturing practices? An influential mapping analysis of multi-company perspective

Highlights

• Focused on the adoption of Sustainable Manufacturing (SM) practices.

• Identified and analysed Human Critical Success Factors (HCSFs) in adoption of SM.

• Conducted a two-phased study to build cause-effect model of identified HCSFs.

• Presented the real-life applicability by taking data from automotive companies.

• Proposed various implications to make strategic plans in the context of SM.

Abstract

Sustainable human factors and change management systems have been gaining significant attention at global level for implementation of sustainable practices within organisations. With the rise in environmental degradation, the automotive sector has made efforts to adopt Sustainable Manufacturing (SM) practices to decrease the adverse effects on the environment instigated by emissions. Human Critical Success Factors (HCSFs) may play an important role in adoption of SM but in literature, no study has yet discussed the influence of HCSFs on the adoption of SM practices. The current work is an effort to fill this gap and to analyse the importance of HCSFs in adopting SM practices from a multi-automotive company perspective. In the first phase study, HCSFs were identified from existing literature and an empirical analysis was carried out to finalise identified HCSFs. In the second phase, to understand the influential relationship among these HCSFs, a DEMATEL approach was employed for developing a cause-effect model for each company. The result suggested that ‘Green motivation’, ‘Customer relationship management’, ‘Management leadership’, ‘Communication’ and ‘Strategic alignment’ are the highly significant causal HCSFs in efficient adoption of SM practices. The results of the study will help industry practitioners and managers to make strategic plans in the context of SM practices and its relationship with human factors for sustainable business development.

Introduction

Rapid growth in industrialisation is leading to growing concerns around climate change problems (Tseng et al., 2018). Changing climatic conditions is recognised as crucial for the global economy (Renukappa et al., 2013). Moreover, this trend is likely to intensify further due to an estimated addition of around three billion customers by 2030 at global level (Mangla et al., 2018). Manufacturing organisations are under enormous pressure to investigate environmental aspects along with economic factors due to the increasing rate of carbon emissions (Hajilary et al., 2018). Therefore, with this rapid increase in natural resource consumption, greenhouse gas emissions, degradation of soil and water etc. sustainability in manufacturing has become a major point of concern (Jabbour et al., 2019; Kumar et al., 2019).

Sustainable organisations aim to achieve lower production costs along with minimisation of harmful effects of their business operations on the environment (Senthilkumaran et al., 2001; Srivastava, 2007; Hajilary et al., 2018). Moreover, due to pressure instilled by the government in the form of statutory requirements, organisations are compelled to adopt green systems (Georgiadis and Vlachos, 2004; Jabbour et al., 2019). For instance, many companies have adopted ISO 140001 (Zhu and Sarkis, 2006). Additionally, positive linkage between business performance and green management practices also drives organisations to adopt green practices and contribute towards reducing carbon emissions by decreasing their carbon footprints (Zhu et al., 2007, 2013; Abdul-Rashid et al., 2017).

Nowadays, business organisations are viewing Sustainable Manufacturing (SM) practices as a strategic initiative. But there are various challenges in implementing SM practices at organisational level (Jabbour et al., 2019) such as economic, social and technological factors. A study conducted by Sindhwani et al. (2019) has described the barriers in adopting green, lean and agile manufacturing practices. Human Critical Success Factors (HCSFs) are observed to be as equally important as other factors such as technology and supply chain initiatives to execute SM practices (Daily and Huang, 2001; de Sousa Jabbour et al., 2018; Kumar et al., 2019). Masri and Jaaron (2017) also observed that green HR practices impact organisations’ environmental performance. Jackson et al. (2011) highlighted the significance of employee support in enabling an organisation to take environmental management initiatives. However, this area of study started to gain importance after some remarkable research highlighted the status of HR practices (Jabbour and de Sousa Jabbour, 2016). Dumont et al. (2017) also observed that green HRM practices impact on employee behaviour directly as well as indirectly. Similarly, in a more recent study conducted by Anthony (2019), employee behaviour is observed to be crucial for the environmental performance of organisations.

Dubey et al. (2017) have indicated that human-related dimensions need to be explored further in order to comprehend their relevance for adoption of green practices. To the best of our knowledge, no study has attempted to model the human related factors in the context of SM practices and hence, a gap exists in current literature. In a more recent study, Prakash et al. (2019) indicated that the Indian economy provides a crucial setting for conducting research that focuses upon environmental aspects of business organisations as it is amongst the fastest growing economies around the globe; to keep up this status, economic activities need to be boosted further through innovation. They also indicated that carbon emissions by India are likely to exert a significant influence on global warming. Yet, environment related studies in the Indian context are very limited. Additionally, India has become an international player in the automobile market. The contribution of this sector to the Gross Domestic Product (GDP) is increasing (The Economic Times, 2017). With growing industrialisation, there are certain factors, such as carbon emissions, which have a negative impact on public health. The Government of India (GoI) has realised this and has picked up the pace in reducing emissions by creating a standard road map for cleaner vehicles and fuels. For instance, the government has announced January 1, 2020 as a deadline to adopt Bharat Stage IV emission norms; subsequently Bharat Stage VI emission norms will place even stricter restrictions on emissions. Therefore, SM practices become even more critical in the context of this industry. Consequently, the current study attempts to explore and model the key HCSFs and their significance in adopting SM practices. The study intends to attain the following objectives:

• To identify key HCSFs for adoption of SM practices

• To assess the listed SM oriented HCSFs by identifying their inter-relationships in adoption of SM practices

• To outline key practical implications and strategies that may facilitate decision makers to achieve a system of SM practices.

The primary aim of the study is to identify the HCSFs related to SM practices and to identify their inter-relationships. In this work, a DEMATEL technique approach for identifying inter-relationships of HCSFs in adoption of SM practices is used. DEMATEL technique (Gabus and Fontela, 1972) helps in evaluating the inter-relationships between HCSFs with the help of an inter-relationship digraph (Hsu et al., 2013; Mangla et al., 2016; Li and Mathiyazhagan, 2018). The case example of multiple Indian automobile companies shows the real-world applicability of the proposed model. The study aims to provide practical implications and strategies to implement SM practices in the workplace.

The entire work of this study is organised into six sections. Section 2 outlines the relevant literature in the area. This is followed by research methodology in Section 3. Analysis and related results are presented in Section 4. Findings are discussed with their practical and theoretical implications in Section 5. Finally, conclusions and future research directions are provided in the last section.