2. Sustainability in Dairy Supply Chain
According to Carter and Rogers
[12][14], when environmental and social aspects of sustainability that extend beyond a firm’s boundary are combined with economic objectives in a deliberate long-term strategy along with the inclusion of SC activities in firm sustainability, it can create a pervasive and less imitable set of processes as well as potential bases for competitive advantage for them and associated chain members. Carter and Rogers
[12][14] define sustainability as a strategic transparent integration of an organization’s social, environmental, and economic goals along with key inter-organizational business processes for improving the individual company’s and its supply chains’ long-term economic performance.
The dairy industry is a major contributor to global warming because of the massive amounts of greenhouse gases (GHGs) it emits
[13][15]. The dairy industry’s greenhouse gas emissions climbed by 18% from 2005 levels to 2015 levels, which is a deep concern for the global environment
[14][16]. The production of these relies heavily on the use of fossil fuels at every stage of the process, which comes mostly from the enteric fermentation of bovine stomach contents
[15][17]. On the other hand, the dairy industry generates 70–80% of the total rural economy as well as 45–55% of employment. Human diets rely heavily on dairy products because they provide a substantial amount of protein and several critical minerals and vitamins, including calcium and vitamin B12
[16][18]. Dairy products (including cheese, milk, and butter) contribute roughly 14% to overall consumption in affluent nations and about 5% in underdeveloped countries in terms of dietary calorie intake
[17][19]. A considerable increase in demand for dairy products raises questions about the sector’s long-term viability considering the rapidly expanding global population, rising per capita income, and “Westernizing” food patterns in the East
[18][20]. In fact, between 2020 and 2030, the market for fresh dairy products is predicted to grow at a compound annual rate of 1.0%.
[18][20]. Despite their nutritional significance, dairy products are produced with a substantially larger carbon footprint than their plant-based counterparts
[19][21]. Low-meat, vegetarian, and vegan diets are on the rise as a result of consumers’ increased concern for environmental impact and animal welfare
[20][22]. In fact, compared to meat eaters, vegans produce around half as many greenhouse gas emissions from their food choices
[21][23]. Therefore, adopting a plant-based diet might significantly aid in the preservation of the natural world. However, with a large number of advantages and disadvantages in the environmental aspects, balance between people, planet, and profit, is required, and hence, sustainable development in the dairy industry is necessary. Towards the development of sustainability, regular performance monitoring is one of the major tasks. Regular sustainability assessment is required for the continuous improvement of sustainable development in the dairy industry. From farmers to markets, there are multiple steps in the dairy supply chain, and at each stage, there are different risk factors that might have an impact on sustainability, as shown below in
Table 1.
Table 1.
Identified Risks factors at each step of the dairy supply chain for sustainability.
3. Sustainable Performance Assessment in Dairy Supply Chain
Most definitions of SPA focus on it being a decision-making aid that prioritizes long-term sustainability. Several studies have applied the TBL concept of sustainability to the food industry to investigate sustainable performance
[22][23][24][12,24,25]. However, many studies evaluating the food industry’s efficacy simply look at sustainability with an environmental focus
[13][25][15,26]. Using a combined Slacks-based measure (SBM) and data envelopment analysis (DEA) technique, Cecchini et al.
[26][27] assessed the environmental performance of dairy companies. Life cycle assessment (LCA) methods have been used to evaluate the environmental impact of the dairy industry
[13][25][27][15,26,28]. The performance impact of the multi-tier supply chain is measured, and a theoretical framework for societal SD was developed by Mohammed et al.
[28][29]. Using a combination of TISM and ANP, Chen et al.
[29][30] created a socially responsible supplier assessment methodology. The analytical methodology and FSC performance metrics were created by Moazzam et al.
[30][31] based on efficiency, flexibility, responsiveness, and quality. Using the notion of the circular economy, Kazancoglu et al.
[31][32] designed a method for evaluating the effectiveness of FSC’s reverse logistics. By bringing together the circular economy, Industry 4.0, and cleaner manufacturing, Gupta et al.
[32][33] designed a hybrid ethical and sustainable business performance paradigm. Barriers to sustainable company operations were examined by Kumar et al.
[33][34] from the viewpoints of Industry 4.0 and the circular economy. With a fuzzy decision-making trial and evaluation laboratory (DEMATEL) based on ANP and TOPSIS approaches, Sufiyan et al.
[34][35] assessed long-term FSC performance. Environmental degradation, social welfare, and economic insecurity were all areas where Bloemhof et al.
[35][36] found that TBL might be utilized in FSC. To reduce carbon dioxide emissions, overall SC costs, and gridlock while still meeting the SDG, the SSC network was built
[36][37].
4. Sustainability KPIs
Given the evolving context and the dynamic nature of environmental, social, and economic aspects, the adoption of new sustainable Key Performance Indicators (KPIs) becomes imperative. These KPIs need to be carefully selected to ensure that they provide a comprehensive assessment of an organization’s performance, encompassing the entire value chain, considering industry-specific context, engaging stakeholders, and aligning with strategic objectives. Choosing the appropriate KPIs is of utmost importance for organizations
[32][33]. Researchers in the field of sustainability assessment have used only TBL dimensions in the past Kumar et al.
[22][12], but Gupta et al.
[32][33] have combined the TBL with Industry 4.0, the circular economy, and clean technology to improve manufacturing organization performance. The six-dimensional approach used by Chen et al.
[29][30] provided that, to choose a socially responsible food provider, one must consider price, longevity, quality, service, communication, and collaboration. Using an integrated, sustainable, and adaptable supply chain as their starting point, Negri et al.
[37][38] created a conceptual framework. Lean, agile, resilient, and sustainable supply chains are the focus of a conceptual framework established by Sharma et al.
[38][39]. When evaluating the effectiveness of a reverse supply chain, Dev et al.
[39][40] use a circular economy approach.
Focusing on social costs influenced by activities like investment in the collection and the size of the end-user market that determines profits is important since they are based on a trade-off analysis between economic and environmental performance and the functioning of I4.0 and circular economy
[39][40]. Past environmental KPIs used by researchers
[40][41] include greenhouse gas emissions, use of water and electricity, green logistics, and more. As a result, economic performance indicators include profit, food quality, logistical efficiency, revenue growth, R&D spending, etc.
[35][41][36,42]. Profit sharing, employee well-being, human resources, supply chain (SC) transparency, gender equity, etc., were all used as social KPIs by researchers
[42][43]. Key performance indicators (KPIs) for CEP in the SSC include waste management, recovery, recycling, and the efficacy of reverse logistics
[43][44] (
Table 2).
Table 2.
Performance indicators with description and source.
5. Tools and Techniques
Sustainability assessment tools may be positioned along three dimensions of the categorization framework established by Morrison-Saunders et al.
[47][48]: (1) underlying sustainability discourses, (2) representations of sustainability within the assessment process, and (3) the decision-making environment. Information creation for decision making, complexity structuring, operationalization, a venue for participation, discussion, and deliberation, and social learning are all goals of SA, as stated by
[48][49]. A further goal of SA, as stated by Moldavska and Welo
[49][50], is “to help decision-makers, simplifying the identification of measures that they should do in the endeavor to contribute to sustainable development.” They added that SA was to alert them of problems that needed fixing within the organization. A review of the relevant literature revealed that researchers have previously employed a wide range of qualitative and quantitative methods to evaluate various outcomes. For environmental sustainability assessment in FSC, several studies have used LCA
[13][15]. While several studies have used data envelopment analysis (DEA) methods to evaluate sustainability
[26][27], others have turned to balanced scorecards
[42][43]. The sustainability assessment of FSC has been conducted using various MCDM methods
[50][51]. Fuzzy TOPSIS was used by Govindan et al. (2013)
[45][46] to rate vendors on their contribution to environmental sustainability. Green SC performance is quantified by Uygun and Dede
[51][52] using a DEMATEL-ANP-TOPSIS hybrid model of the MCDM. The SCOR model may be connected to supply chain performance indicators such as dependability, responsiveness, flexibility, cost, asset metrics, and sustainability
[52][53]. SCOR is a methodology for measuring the environmental effect of an organization’s supply chain activities in terms of its capacity for sustainability and natural resource management
[52][53]. Because the SRPM framework’s practical applicability is dependent on a resource-based perspective, the SCOR model is used to clearly align the business processes and activities (i.e., plan, source, make, deliver, and return) as firm resources are important in identifying the scope for socio-economic and socio-environmental sustainability.