Corporate Sustainability Due Diligence: Insights from a survey of industrial companies in Austria
Gerald Feichtinger1, Karl Friedrich1,2, Wolfgang Posch1
1Chair of Economic and Business Management, Montanuniversitaet Leoben, Austria; 2Chair of Mineral Processing, Montanuniversitaet Leoben, Austria
Introduction
The globalization of the international economic system and the progress made in the field of information and communication technologies have led to the development of very extensive trade networks. The accompanying unbundling of production systems, driven by low transport costs, has accelerated the diversification towards global supply and value chains. This well-intentioned idea to promote global economic development led to a relocation of production facilities towards economically favorable regions, in particular emerging and developing countries with mostly low social and environmental standards. As a result of that, the United Nations (UN, 2011) and, subsequently, the OECD (2016, ongoing) adopted guidelines on respecting responsibilities in the global supply chains.
However, international regulations are needed ensuring compliance with due diligence obligations along global supply chains. Various European countries (e.g., Germany) have already adopted regulations, which is why companies in Austria, for example, are already indirectly obliged with corporate due diligence obligations. The EU adopted its Corporate Sustainability Due Diligence Directive (CSDDD) in 2024 which will act as a harmonized legal framework. Its most important goals include, among others, the reduction of human rights related and environmental risks along supply chains and ensuring compliance with the 1.5°C climate target.
This paper deals with the potential effects of regulations which focus on due diligence obligations along the supply and value chains of companies. Based on a survey supplemented by structured in-depth interviews with companies and interviewees in Austria, a critical assessment of existing and upcoming legislation is presented.
Methodological approach
Based on a literature review, a mixed approach consisting of an online survey and supplementary in-depth interviews was chosen as the underlying research method. A compact, yet broadly based questionaire was developed for the online-survey, which comprises a total of 24 questions consisting of single choice, multiple choice and open text questions divided into seven sections. In addidtion to two general chapters on company key figures, comments and contact data, five content-based sections have been considered: introduction to legal aspects, human right related risks, environmental risks, risk management and challenges/risks and chances/opportunities associated with the due diligence acts. A guideline has also been developed for the structured in-depth interviews in order to obtain specific additional information regarding the survey from the interviewees.
Preliminary results
This survey with various partners among companies in Austria will run until the end of June 2024, which is why only a few preliminary results can be analyzed at present. Among the companies survey it turned out, that only a few companies were aware of existing regulations. Some of the supply chain laws surveyed are at least partially known, e.g., the Corporate Sustainability Due Diligence Directive (CSDDD), Conflict minerals regulation (CMR) from EU and USA, Supply Chain Acts from Germany and Switzerland. Others regulations from Norway, the Netherlands, Australia, France and Great Britain are, however, rather unknown. Further results will follow.
Road Safety Re-defined: Improving Transportation Safety through Artificial Intelligence and Human-centered Data Analytics regarding Truck Driver Work Settings
Matthias Klumpp1,2, Maria Keil2, Caroline Ruiner3, Sarah M. Straub3, Vera Hagemann4, Arnd Meiser4, Marc Hesenius5, Benedikt Severin5
1Politecnico di Milano, Italy; 2TU Darmstadt, Germany; 3University of Hohenheim, Germany; 4University of Bremen; 5University of Duisburg-Essen
Purpose
Truck drivers are a central occupational group within transportation, including about 4.5 million persons within the EU. A major focus in transportation research is safety (Barnett, 2020; Schindler & Bianchi Piccinini, 2021). Existing approaches examined for example sleep patterns (Cai et al., 2021; Onninen et al., 2021) or physical stress (Sekkay et al., 2020) in relation to road accidents. However, mental stress of drivers is increasing due to external time pressure or increased technological complexity (Kamzanova et al., 2014), as is the lack of drivers caused by this and bad working conditions. For this reason, research with a human-centered approach is duely needed. This paper analyzes human factor issues influencing safety in order to contribute to improved conceptual frameworks for road transportation safety.
Approach
Since road traffic is a cybernetic model consisting of subsystems, a mixed-methods approach is used. Human behaviour plays a central role in the occurrence of accidents (Lajunen et al., 2004). Therefore, we use a mixed-method design including interviews to identify both objective and subjective factors which indicate human driver stress. To this end, we combine various vital parameter quantitative data with qualitative interviews. Heart rate variability as a neurocardiac function reflects the heart-brain interaction (Perrone et al., 2021) and can therefore be used as an indicator of mental stress (Taelman et al., 2011). For this reason, a mobile ECG was applied. In addition, the brain exhibits a course of alpha spindles, which reflect the neurological function of alertness (Schmidt et al., 2009). Therefore, a mobile cEEGrid is used as examination method (Bleichner & Emkes, 2020). During stress, cortisol is released (Aguilar Cordero et al., 2014). It is one of the best-known hormones for stress assessment (Antoun et al., 2017) and is analyzed by taking saliva samples. Truck drivers are particularly exposed to external stress factors (Shattell et al., 2010). These include, for example, the driving itself, the behavior of other drivers, visibility, and weather conditions, also collected in the course of this study (Hill & Boyle, 2007). All data is time-stamped to enable synchronization and qualitative interviews were conducted with drivers. These are analyzed in a rule-guided and systematic way (Mayring, 2000). We then use supervised learning methods of AI to identify stressful situations.
Findings
The survey data is diverse, with enclosed Figure 1 showing a small extract. At the top left is an excerpt from the ECG of a driver journey. The top right shows the number of alpha spindles recorded by different drivers over the course of the ride. The changes in a driver’s pulse rate and HRV in different traffic situations are shown at the bottom. The other data was also processed individually and analyzed by machine learning applications. The investigation has brought several new insights. This innovative approach shows that by collecting human-centered data in combination with the use of artificial intelligence, stressful factors can be identified. This approach can contribute to healthier work for truck drivers and an increase in road safety.
Embracing Sustainability along Supply Chains: The role of internal and external drivers among manufacturing firms in Mwanza, Tanzania
Edward Bahati Makoye, Sarah Muhoja Clavery
Mzumbe University, Tanzania
The rapid global development in Science and Technology has fuelled economic globalization. This tendency has put pressure on available resources flowing through global supply chains. Supply chains are not only considered as carriers of resources from upstream through to downstream the firm but also strategic assets for competition. To sustain their competitiveness, firms are forced to embrace environmental and social concerns in addition to mainstream economic motives. Research has indicated that firms from both developed and developing countries adopt sustainability practices from varied perspectives (Saeed & Kersten, 2019). There is scanty literature on sustainability in developing countries due to infancy of the sustainability agenda as opposed to the developed world. While Northern researchers focus on matters such as carbon gases emissions and carbon footprint measures and private certifications as remedial actions for reducing impacts of both industrial and human-made greenhouse gases (GHGs) and similar climate change agents (Wakamatsu and Maruyama, 2024; Tsutsumi, Furukawa and Kitamura, 2024; Blanco, 2021; Boukherroub et al., 2017; Jairo et al., 2015), their counterparts in the South are still uncertain and lagging behind except for Brazil, China and India (Saeed and Kersten, 2019:9).
We argue that knowledge about China, Brazil and India does not warrant generalizability for all developing countries. Hence we pose the following research question: which factors determine sustainability adoption by manufacturing firms operating in Tanzania? Responding to this question will contribute to an invaluable understanding of the dynamics involved between developing and developed countries not only because of eminent differences in market conditions but also obvious departures in the rules and standards exercised by the ‘two worlds’.
Theoretically, the study treats sustainability adoption as an innovation and therefore deploys the diffusion of innovation (DOI) theory. Through DOI it is assumed that manufacturing firms initiate sustainable practices and export (diffuse) them to trading partners along the chain. Chain members will adopt them because the prevailing conditions both internally and externally.
Our sample comprised a total of 106 firms which were drawn among first tier supplier and customer firms with manufacturing firms providing recommendations. We collected the data through a questionnaire. We also supplemented our data by conducting interviews with selected company executives and browsing on company web pages. A regression analysis through a probit model was used to analyze the quantitative data while qualitative information was analyzed thematically.
Findings indicate that most firms have adopted sustainable practices along their supply chains. They attributed their adoption to compatibility, external pressure and relative advantage as key factors. The same are significantly and positively related to adoption of sustainable supply chains in the model. However, supply chain complexity is not a significant determinant for adoption. These findings point to policy in two ways. First, policies made to guide the industrialization process should require businesses to internalize sustainability practices right from their inception rather than later. Second, even though the results could be generalized across industries, it is recommended that regulatory enforcement should focus on industry-specific characteristics as sustainability uptake differs across the studied industries.
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