Safety Failure Factors Affecting Dairy Supply Chain: Insights from a Developing Economy

Sustainable construction through energy management practices: an integrated hierarchal framework of drivers in the construction sector

Reducing energy usage and promoting energy management practices remain hot issues in the construction sector. Construction firms are not interested to adopt energy conservation and management practices in their projects. Despite the successful integration of energy management practices in developed nations, their adaptability in developing countries, especially in Pakistan, is at a slow pace. Therefore, drivers to energy management practices need to be realized for its adoption. Based on this, the current study intends to evaluate the drivers of energy management practices adopted in the construction sector of Pakistan by using a four-stage methodology. Fuzzy Delphi method (FDM), interpretive structural modeling (ISM), and Matrice d'Impacts Croises Multiplication Appliques a un Classement (MICMAC) analysis were integrated with prioritizing essential drivers. Increased tax imposition on construction companies for energy usage and pollution contribution, promotion of investment subsidies for energy efficiency technologies, and increased enforcement of government rules and regulations regarding on-site energy management practices arose as significant drivers to adoption of energy management practices in the construction sector of Pakistan. These results will be helpful for policymakers to develop effective policies for integrating energy management practices in the construction sector. This study contributes significantly by developing a novel model of drivers affecting EMP adoption in the Pakistani construction sector. Further research might be expanded to other developing countries to validate current results.

Blockchain-Enabled Supply Chain platform for Indian Dairy Industry: Safety and Traceability

Conventional food supply chains are centralized in nature and possess challenges pertaining to a single point of failure, product irregularities, quality compromises, and loss of data. Numerous cases of food fraud, contamination, and adulteration are daily reported from multiple parts of India, suggesting the absolute need for an upgraded decentralized supply chain model. A country such as India, where its biggest strength is its demographic dividend, cannot afford to malnutrition a large population of its children by allowing them to consume contaminated and adulterated dairy products. In view of the gravity of the situation, we propose a blockchain-enabled supply chain platform for the dairy industry. With respect to the supply chain platform, the dairy products of choice include milk, cheese, and butter. Blockchain is one of the fastest growing technologies having widespread acceptance across multiple industry verticals. Blockchain possesses the power to transform traditional supply chains into decentralized, robust, transparent, tamper proof, and sustainable supply chains. The proposed supply chain platform goes beyond the aspect of food traceability and focuses on maintaining the nutritional values of dairy products, identification of adulteration and contamination in dairy products, the increasing economic viability of running a dairy farm, preventing counterfeit dairy products, and enhancing the revenue of the dairy company. The paper collates the mentioned functionalities into four distinct impact dimensions: social, economic, operations, and sustainability. The proposed blockchain-enabled dairy supply chain platform combines the use of smart contracts, quick response code (QR code) technology, and IoT and has the potential to redefine the dairy supply chains on socio-economic, operational, and sustainability parameters.

Global Dairy Sector: Trends, Prospects, and Challenges

Currently, there is a strong need to find practical solutions towards meeting the expected efficiency and overcoming recurring sustainability challenges in the global dairy sector [...]

Seaport Terminals Risks Prioritization Using a Structural Modeling-Based Approach: A Real Case Study

Port risk management (PRM) during port operations is a current problem that can negatively affect the environment, people, and economic issues. In the literature, there is an enormous amount of research related to supply chain risk management (SCRM) in various areas and with various objectives. However, PRM has not received the same degree of attention. In fact, port terminals are crucial links in most supply chain networks and an important pillar of international trade. Therefore, for better risk mitigation efficiency, a risk assessment and prioritization step are vital. Recently in the literature, researchers have applied prospective methods such as structural analysis methods to risk prioritization in SCRM. The aim of this research is to prioritize various man-made risk variables in PRM using a qualitative structural modeling-based approach, specifically, the MICMAC method (referring to its French acronym: Matrice d’Impacts Croisés Multiplication Appliquée à un Classement). An empirical study was conducted to assesses and prioritize risk variables of the seaport terminals of Sfax (Tunisia). The main contributions of the empirical research are twofold. First, to prioritize the key risk variables to define the most critical ones that require immediate intervention. Second, to analyze the structure of the influences between all identified risk variables. The results for the port terminals of Sfax show that the highest-priority risk variables are the manual handling (Ph3), disregard for safety aspects (Ph4), unsafe storage of goods (Inc1), absence of a prevention system and a rescue organization (Inc2), neglect of the regulatory aspects of handling equipment (M1), ignorance of good handling practices during the operation of loading and unloading (Cho2), and inadequate lifting accessories (Cho3). These risk variables must be the subject of urgent risk reduction strategies.

Circular dairy supply chain management through Internet of Things-enabled technologies

Internet of Things-enabled technologies help to collect data and make it understandable, especially in supply chain processes, thus minimizing the problems that may arise in supply chains. It is extremely important to support this process with Internet of Things-enabled technologies, especially in supply chains that are vulnerable to disruptions such as the dairy supply chain. Moreover, dairy supply chains are the type of supply chains where the most waste is generated; evaluating this waste is very beneficial to the circular economy. Therefore, monitoring data in dairy supply chains and using Internet of Things-enabled technologies prevent losses; it is critical to have Internet of Things-enabled circular dairy supply chains in operation. The aim of this study is to determine the success factors of Internet of Things-enabled circular dairy supply chains based on the various stages of these chains; we hope to match each dairy supply chain stage with a success factor of Internet of Things-enabled technology and determine a ranking for these factors. Hence, six success factors of Internet of Things-enabled circular supply chains are weighted for each stage of the chain; Internet of Things-enabled digital technologies are then matched with each stage of the chain, and the success factor is determined. The ranking of factors can then be drawn up through the integration of Step Wise Weight Assessment Ratio Analysis (SWARA) and Technique for Order Preference Similar to Ideal Solution (TOPSIS). The outcome of this study will provide managers and policy makers with insights into Internet of Things-enabled circular dairy supply chains.