Transportation is one of the most important functions of logistics management because of its impact on both the level of customer service provision and the organization’s cost structure. The study explores the transportation cost optimization strategies and how they affect the supply chain performance of Shea nuts in the Agro-processing industries in Ghana. The quantitative study design was adopted and utilized to solicit data. With a sample size of 204 respondents. Data was analyzed using multiple linear regression in Statistical Package for Social Sciences (SPSS v20). The results revealed interesting findings in the supply chain within the institution as it seeks to assert that transportation is seen to be effective and contribute highly to firms output when Agro companies use outsourcing and pooling as means of transport. From the results, the supply chain correlated positively and significantly with outsourcing and pooling as transport optimization practices in Agro firms supply chain. This paper adds to the existing literature on the supply chain systems of Agro processing firms but departs from previous studies which seek to concentrate not on the transport optimization of the Agro processing firms but rather on the challenges, production, and profit maximization of these firms. Our study is unique unlike any other research previously authored as it seeks to reveal the option of transport optimization that is cost effective and efficiently productive for Agro processing firms to adopt.

Sustainability is getting preference now-a-days in most of the countries in the world. This implies industrial and other developments for economic growth, and of course civilization, but certainly not at the cost of environmental degradation. Environmental conservation is a must. One of the major components of industrial sectors is their electrical energy inputs through electrical substation. Numerous research addresses the issue of energy pollution, cantering on fossil fuel. A very few research can be found which address the issue of pollution generated from electrical energy. This research addresses this issue, with special attention to electrical substations. In the last two or three decades, several electrical equipment manufacturers have started producing this equipment in Bangladesh, which were previously import-oriented. This equipment use various types of oils, acids, zinc and other metals, which are all environmentally hazardous. Thus, any industrial company, buying such equipment from substation manufacturers, should consider green aspects. As such, now it is of prime importance to select green suppliers of substation equipment. Since selection of right or green supplier involves multi-criteria evaluation, Multi-criteria Decision Making (MCDM) technique is essential. Additionally, both qualitative and quantitative criteria require fuzzy analysis to make it more precise and realistic. This research addressed the issue of environmental pollution, its sources, nature and severity, and their mitigation through selecting green suppliers.

With increasing economic instability coupled with climate change and the Covid-19 pandemic the subject of economic resilience in agripreneurship value chains in rural farming has gained prominence. Despite the constant engagements on the subject, there still is a missing piece on the determinants of economic resilience and sustainability for agripreneurship in tobacco value chains. The objective of this study was to characterize rural farming typologies which will assist in determining resilience and sustainability for tobacco value chains. The research adopted a pragmatic research approach, where quantitative results were triangulated with qualitative results to test the robustness of the research findings. A total of 250 questionnaires were administered to small scale tobacco farmers in Gokwe and interviews were held with selected 8 Agri-tex-officers. STATA version 12 was used to analyse quantitative data and thematic analysis using vignettes for qualitative data. The research findings showed a significant positive relationship between sustainable agripreneurship and economic resilience in tobacco farming in Gokwe district. The study recommends that the government prioritise the development of sustainable tobacco infrastructure throughout the value chain and training of tobacco farmers on resilient farming methods. This study offers theoretical contributions on how to achieve economic resilience and sustainable agripreneurship in tobacco value chains in Gokwe district.

Making rational decisions in times of uncertainty is an important capability required of marketing managers. However, choosing the precise quantitative decision-making technique or a combination of such tools usually presents managers with a score of challenges. To lessen this challenge, this single case research demonstrates how the choice of three Bayesian decision models (Laplace criterion, Savage minimax regret, and Hurwicz coefficient of realization) can reduce uncertainty in content marketing, search engine optimization (SEO), and referral marketing decision. We employed the case study approach to enable direct access to the decision-making process of the case organization, and to collect relevant data relating to the three marketing decision variables. Results show that, although the Laplace criterion may not have a direct effect on content marketing decisions, it influences the decision-making process leading to the creation and promotion of content. The Savage minimax regret had a direct bearing on SEO decision-making. Hurwicz's coefficient of realization yielded no direct impact on referral marketing but shows the possibility of influencing decision-making processes that led to the development and implementation of referral marketing campaigns. The implications are discussed.

The uprising of blockchain technology has recently become a trend owing to its prowess to reform the governance of supply chains, offering improved levels of data transparency, traceability, and efficient workflow. The objective drawn on this research is to examine the key determinants that impact the adoption as well as applicability of blockchain technology within the supply chain management context. The Decision-Making Trial and Evaluation Laboratory (DEMATEL) model is tested in this study to inspect and fathom the complex relationships between these components, thereby uncovering their respective significance and interrelationships. The results derived from this study contribute vital insights into the ever-changing landscape of blockchain adoption, with a particular focus on key factors comprising technical competencies, IT infrastructure, interoperability, compatibility, and complexity. The research based on DEMATEL methodology reveals both direct and indirect influences, facilitating a more comprehensive comprehension of these crucial variables. This study is an invaluable resource for industry stakeholders, policymakers, and organizations seeking to embrace blockchain technology into supply chain operations. This study’s original intent is to frame an extensive analysis of the key aspects and their interrelationships, offering valuable insights for making well-informed decisions. The overarching aim is to facilitate the seamless assimilation of blockchain architecture into supply chain management systems, promoting effectiveness along with harmony.